Advancements in medical treatment for pancreatic neuroendocrine tumors:A beacon of hope

This editorial highlights the remarkable advancements in medical treatment strategies for pancreatic neuroendocrine tumors(pan-NETs),emphasizing tailored approaches for specific subtypes.Cytoreductive surgery and somatostatin analogs(SSAs)play pivotal roles in managing tumors,while palliative options such as molecular targeted therapy,peptide receptor radionuclide therapy,and chemotherapy are reserved for SSA-refractory patients.Gastrinomas,insul-inomas,glucagonomas,carcinoid tumors and VIPomas necessitate distinct thera-peutic strategies.Understanding the genetic basis of pan-NETs and exploring immunotherapies could lead to promising avenues for future research.This review underscores the evolving landscape of pan-NET treatment,offering renewed hope and improved outcomes for patients facing this complex disease.

A cross-sectional study to assess medication safety,knowledge,attitude,and practices regarding nutrition and medication among pregnant women

Objective:To assess pregnant women's knowledge,attitude,and practice regarding nutrition and medication usage,analyse the prescribing pattern,and categorize them based on the Food and Drug Administration(FDA)guidelines.Methods:A cross-sectional study was conducted with 264 pregnant women in the obstetrics and gynaecology department of a tertiary care hospital from October 2022 to August 2023.A knowledge,attitude,and practice(KAP)questionnaire was prepared in English language by the researchers and validated by an expert panel consisting of 12 members.The validated questionnaire was then translated into regional languages,Kannada and Malayalam.The reliability of the questionnaire was assessed with test-retest method with a representative sample population of 30 subjects(10 subjects for each language).The subjects'knowledge,attitude,and practice were evaluated using the validated KAP questionnaire.The safety of the medication was assessed using the FDA drug safety classification for pregnancy.Results:The mean scores for nutritional and medication usage knowledge,attitude,and practice were 4.14±1.15,4.50±1.09,and 3.00±1.47,respectively.Among 30 prescribed medications,3 belong to category A(no risk in human studies),8 belong to category B(no risk in animal studies),18 belong to category C(risk cannot be ruled out)and 1 drug is not classified.A significant association was observed between medication knowledge and practice(r=0.159,P=0.010).Conclusions:Most of the study population knows the need to maintain good dietary and medication practices during pregnancy.Counselling pregnant women regarding diet and medication usage is crucial in maternal care.

Mediating role of inner strength in the relationship between medication literacy and medication adherence among kidney transplant patients

Objective:Compared with long-term renal replacement therapy,kidney transplantation is the ideal treatment for end-stage renal disease(ESRD),significantly extending patient life and improving quality of life.Kidney transplant patients need to adhere to lifelong immunosuppressive medication regimens,but their medication adherence is generally poor compared with other organ transplant recipients.Medication adherence is closely related to medication literacy and psychological status,yet related studies are limited.This study aims to investigate the current status of medication adherence,inner strength,and medication literacy in kidney transplant patients,analyze the relationships among these 3 factors,and explore the mediating role of inner strength in the relationship between medication literacy and medication adherence.Methods:A cross-sectional survey was conducted from March to October 2023 involving 421 patients aged≥18 years who visited kidney transplantation outpatient clinics at 4 tertiary hospitals in Hunan Province.The inner strength,medication literacy,and medication adherence of kidney transplant patients were investigated using the Inner Strength Scale(ISS),the Chinese version of the Medication Literacy Assessment in Spanish and English(MedLitRxSE),and the Chinese version of the Morisky Medication Adherence Scale-8(C-MMAS-8),respectively.Univariate analysis was performed to examine the effects of demographic and clinical data on medication adherence.Correlation analysis was conducted to explore the relationships among medication literacy,medication adherence,and inner strength.Significant variables from univariate and correlation analyses were further analyzed using multiple linear regression,and the mediating effect of inner strength was explored.Results:Among the 421 questionnaires collected,408 were valid,with an effective rate of 96.91%.The scores of C-MMAS-8,MedLitRxSE,and ISS were 6.64±1.16,100.63±14.67,and 8.47±4.03,respectively.Among the 408 patients,only 86(21.08%)patients had a high level of medication adherence,whereas 230(56.37%)patients had a medium level of medication adherence,and 92(22.55%)patients had poor medication adherence.Univariate analysis indicated that the kidney transplant patients’age,marital status,education levels,years since their kidney transplant operation,number of hospitalizations after the kidney transplant,and adverse drug reactions showed significant differences in medication adherence(all P<0.05).Correlation analysis showed that inner strength positively correlated with both medication literacy(r=0.183,P<0.001)and medication adherence(r=0.201,P<0.001).Additionally,there was a positive correlation between medication adherence and medication literacy(r=0.236,P<0.001).Inner strength accounted for 13.22%of the total effect in the mediating role between medication literacy and medication adherence.Conclusion:The level of medication adherence among kidney transplant patients needs improvement,and targeted intervention measures are essential.Inner strength mediates the relationship between medication literacy and medication adherence in these patients.Healthcare professionals should focus on enhancing medication literacy and supporting patients’inner strength to improve medication adherence.

Tumor microenvironment reprogramming by nanomedicine to enhance the effect of tumor immunotherapy

With the rapid development of the fields of tumor biology and immunology, tumor immunotherapy has been used in clinical practice and has demonstrated significant therapeutic potential, particularly for treating tumors that do not respond to standard treatment options. Despite its advances, immunotherapy still has limitations, such as poor clinical response rates and differences in individual patient responses, largely because tumor tissues have strong immunosuppressive microenvironments. Many tumors have a tumor microenvironment (TME) that is characterized by hypoxia, low pH, and substantial numbers of immunosuppressive cells, and these are the main factors limiting the efficacy of antitumor immunotherapy. The TME is crucial to the occurrence, growth, and metastasis of tumors. Therefore, numerous studies have been devoted to improving the effects of immunotherapy by remodeling the TME. Effective regulation of the TME and reversal of immunosuppressive conditions are effective strategies for improving tumor immunotherapy. The use of multidrug combinations to improve the TME is an efficient way to enhance antitumor immune efficacy. However, the inability to effectively target drugs decreases therapeutic effects and causes toxic side effects. Nanodrug delivery carriers have the advantageous ability to enhance drug bioavailability and improve drug targeting. Importantly, they can also regulate the TME and deliver large or small therapeutic molecules to decrease the inhibitory effect of the TME on immune cells. Therefore, nanomedicine has great potential for reprogramming immunosuppressive microenvironments and represents a new immunotherapeutic strategy. Therefore, this article reviews strategies for improving the TME and summarizes research on synergistic nanomedicine approaches that enhance the efficacy of tumor immunotherapy.

Research on Multi-Scale Feature Fusion Network Algorithm Based on Brain Tumor Medical Image Classification

Gliomas have the highest mortality rate of all brain tumors.Correctly classifying the glioma risk period can help doctors make reasonable treatment plans and improve patients’survival rates.This paper proposes a hierarchical multi-scale attention feature fusion medical image classification network(HMAC-Net),which effectively combines global features and local features.The network framework consists of three parallel layers:The global feature extraction layer,the local feature extraction layer,and the multi-scale feature fusion layer.A linear sparse attention mechanism is designed in the global feature extraction layer to reduce information redundancy.In the local feature extraction layer,a bilateral local attention mechanism is introduced to improve the extraction of relevant information between adjacent slices.In the multi-scale feature fusion layer,a channel fusion block combining convolutional attention mechanism and residual inverse multi-layer perceptron is proposed to prevent gradient disappearance and network degradation and improve feature representation capability.The double-branch iterative multi-scale classification block is used to improve the classification performance.On the brain glioma risk grading dataset,the results of the ablation experiment and comparison experiment show that the proposed HMAC-Net has the best performance in both qualitative analysis of heat maps and quantitative analysis of evaluation indicators.On the dataset of skin cancer classification,the generalization experiment results show that the proposed HMAC-Net has a good generalization effect.

Informing policy makers in developing countries:Practices and limitations of geriatric home medication review in Malaysia-A qualitative inquiry

Objective:To explore existing practices and challenges in the delivery of geriatric home medication review(HMR).The study was part of a larger study aimed to offer solution to expand the range of geriatric HMR.Methods:This study employed qualitative exploratory design through semi-structured individual in-depth interviews with the public pharmacists involved in the delivery of geriatric HMR at public hospitals.The purpose of the interviews was to explore challenges faced by them in the delivery of geriatric HMR.Results:Based on the emerging themes from the qualitative data,the study reveals that geriatric HMR in Malaysia is integrated as part of multidisciplinary home care visits,encompassing a diverse patient population with various healthcare needs.However,it faces challenges such as the lack of outcome monitoring,formal training,and workforce constraints.Despite these hurdles,there is a pressing need for the expansion of this service to better serve the community,and collaboration with community pharmacists holds potential to broaden its scope.Ultimately,the findings suggest that pharmacist-led HMR is both warranted and feasible within the Malaysian healthcare context.In order to optimize medicine-use among older people living in the community,approaches for expanding geriatric HMR services in Malaysia must be developed.Conclusions:This study holds profound implications as it attempts to illuminate policy makers in developing countries,enabling them to formulate effective HMR plans.By considering the challenges highlighted within this research,policy makers can design a comprehensive HMR service that caters adeptly to the healthcare needs of the mass population.

Advancements in Medication Rule for Pulmonary Nodules: A Review of Current Research Progress

This paper reviewed the literature on medication rule of pulmonary nodules in recent years. It is found that contemporary doctors pay more attention to regulating Qi, clearing heat and detoxifying, eliminating phlegm, dissolving phlegm and dissipating masses. They use mild drugs, cold and warm treatments in parallel, combining the tastes of pungent, bitterness, and sweetness at the same time. The treatment focuses on the five viscera with emphasis on the lung meridian while also considering the spleen and stomach functions as well as soothing liver stagnation. This information aims to provide some reference for clinical treatment of pulmonary nodules.

Research Progress of Measuring Tools for Patient Medication Compliance

This paper introduced the content, compilation process, reliability and validity, scoring method of the evaluation tool for patients’ medication compliance at home and abroad, and reviewed the research progress of the tool. The evaluation method, dimension, scoring method, evaluation content and application scope of the tool were compared, so as to provide reference for nurses to comprehensively and accurately evaluate patients’ medication status.

Exploring the limited use of transdermal medications in psychiatry:Challenges and potential solutions

Transdermal medications are an useful yet underutilized tool in the field of psychiatry.Despite numerous advantages of using this route of medication delivery,transdermal medications remain less popular compared to other routes of medication administration such as oral and intramuscular routes in the management of various psychiatric conditions.In this editorial,we examine the advantages of transdermal medications with a brief overview of transdermal being used in psychiatry and other medical specialties.We discuss the factors that play a role in their limited usage in psychiatry.We highlight certain patient categories who can specifically benefit from them and discuss potential solutions that can broaden the perspective of treating clinicians making this an intriguing avenue in the field of psychiatry.

Adaptive Modeling of Monthly Depression Levels in Terms of Daily Assessments of Opioid Medications Taken and Pain Levels for Cancer Patients

A research study collected intensive longitudinal data from cancer patients on a daily basis as well as non-intensive longitudinal survey data on a monthly basis. Although the daily data need separate analysis, those data can also be utilized to generate predictors of monthly outcomes. Alternatives for generating daily data predictors of monthly outcomes are addressed in this work. Analyses are reported of depression measured by the Patient Health Questionnaire 8 as the monthly survey outcome. Daily measures include numbers of opioid medications taken, numbers of pain flares, least pain levels, and worst pain levels. Predictors are averages of recent non-missing values for each daily measure recorded on or prior to survey dates for depression values. Weights for recent non-missing values are based on days between measurement of a recent value and a survey date. Five alternative averages are considered: averages with unit weights, averages with reciprocal weights, weighted averages with reciprocal weights, averages with exponential weights, and weighted averages with exponential weights. Adaptive regression methods based on likelihood cross-validation (LCV) scores are used to generate fractional polynomial models for possible nonlinear dependence of depression on each average. For all four daily measures, the best LCV score over averages of all types is generated using the average of recent non-missing values with reciprocal weights. Generated models are nonlinear and monotonic. Results indicate that an appropriate choice would be to assume three recent non-missing values and use the average with reciprocal weights of the first three recent non-missing values.

Clinical effects of detailed nursing management interventions on medication adherence and disease perception in patients with drugresistant tuberculosis

BACKGROUND Tuberculosis(TB)is a chronic respiratory infectious disease that considerably jeopardizes human health,and there is no effective vaccine suitable for its prevention in the entire population.AIM To investigate the promotion of medication adherence and disease cognition in patients with drug-resistant(DR-)TB using detailed nursing management.METHODS In total,114 patients with DR-TB who were diagnosed and treated at our hospital between January 2019 and January 2023 were included in this study.Patients in the control group(n=57)were managed with conventional nursing care,while those in the observation group(n=57)were managed with detailed nursing care.Medication adherence,disease awareness scores,medication safety,and nursing satisfaction were compared between the two groups after the intervention.RESULTS The post-intervention medication compliance rate was 91.23%in the observation group and 75.44%in the control group,with the former being 15.79%higher than the latter(P<0.05).There was no statistically significant difference in the disease awareness scores between the two groups before the intervention;the disease awareness scores of the observation group were significantly higher than those of the control group after the intervention(P<0.05).The incidence of gastrointestinal reactions,joint swelling and pain,hearing loss,electrolyte disorders,and liver and kidney function abnormalities were lower in the observation group than those in the control group.The total nursing satisfaction of the observation group was higher than that of the control group(P<0.05).CONCLUSION Implementation of detailed nursing management for patients with DR-TB can effectively improve medication adherence,enhance awareness of the disease,ensure safety of medication,and improve satisfaction with nursing care.

Effect of comprehensive intervention model based on drugpsychology-society-skills on medication compliance and cognitive ability of chronic schizophrenia patients

BACKGROUND The intervention value of a drug-psycho-social-skill model on medication compliance and cognitive ability in patients with chronic schizophrenia was unknown.AIM To explore the intervention value of a drug-psycho-social-skill model on medication compliance and cognitive ability in patients with chronic schizophrenia.METHODS Overall,98 out-patients and in-patients with chronic schizophrenia treated in our hospital from February 2022 to January 2023 were included and randomly divided into the study(50 patients)and control groups(48 patients).For 3 months,the control group was treated with conventional drugs,and the research group with a comprehensive intervention model of drug-psychology-society-skills.Data were obtained for the mini mental assessment scale(MMSE),Montreal cognitive assessment scale(MoCA),positive and negative symptom scale,insight and treatment attitude scale,cognitive ability scale and social skills[personal and social function scale(PSP)].The adverse reactions were observed.RESULTS After the intervention,the MMSE and MoCA scores improved in both groups.MoCA scores in the study group(26.58±3.21)were significantly(P<0.05)higher than those in the control group(24.68±3.02),MMSE scores were not significantly higher.Post-intervention,positive and negative symptom scores improved in both groups,and the positive and negative symptom scores in the study group[(12.01±2.58)and(32.51±2.11)]were significantly(P<0.05)different than those in the control group[(14.54±2.33)and(33.74±2.55)].Post-intervention,insight and treatment attitudes questionnaire scores of both groups were improved and compared with the control group(7.97±3.02),the study group(13.56±6.35)had significantly(P<0.05)higher scores.Post-intervention,the MATRICS consensus cognitive battery score of both groups was improved and compared with the control group(38.44±6.23),the score of the study group was significantly(P<0.05)increased(43.51±6.01).Post-intervention,the PSP score of the study group(78.38±6.63)was significantly(P<0.05)higher than that of the control group(74.52±7.01).During the intervention period,the incidence of adverse reactions in the study group was 6.25%,not significantly different from that in the control group(8.33%).During the intervention,both groups experienced adverse reactions,with no significant difference between groups(P>0.05).CONCLUSION The comprehensive intervention model based on drug-psychology-society-skills has obvious intervention effects on patients with chronic schizophrenia,which improves their cognitive ability and reduces their positive and negative symptoms.Simultaneously,it improves the self-knowledge of patients,improves their attitude toward treatment,effectively promotes the recovery of patients'social functions,and is safe.Therefore,it is worthy of being vigorously promoted and widely used in clinics.

Study on the Medication Rules of Traditional Chinese Medicine Prescriptions for the Treatment of New Crown Pneumonia Based on Data Mining Technology

[Objectives]This study was conducted to analyze the medication rules of clinical prescriptions of traditional Chinese medicine decoction pieces for the treatment of novel coronavirus pneumonia(COVID-19)during the epidemic in multiple regions based on data mining technology,so as to provide a reference for the treatment of COVID-19 with traditional Chinese medicine.[Methods]The traditional Chinese medicine prescriptions used since the outbreak of COVID-19 in Hubei Province during the fight against the epidemic from February 25,2020 to February 14,2022,the traditional Chinese medicine prescriptions used by Guizhou traditional Chinese medicine expert team aiding Hubei Province,the traditional Chinese medicine prescriptions for rehabilitation and conditioning of patients in Ezhou of Hubei Province after discharge,the traditional Chinese medicine prescriptions for the prevention and treatment of COVID-19 in Guizhou Province,and the traditional Chinese medicine prescriptions for the treatment of COVID-19 collected from the end of 2019 to the present from the Chinese database of CNKI were collected as the data of this study.Excel was used to establish a database and enter it into the TCM inheritance calculation platform V3.5,and the association rules and k-means clustering algorithm were used to analyze the frequency of herbal medicines in prescriptions during the treatment of COVID-19,the frequency of four natures,five flavors,meridian distribution,and drug combinations.[Results]A total of 1859 COVID-19 patients treated with traditional Chinese medicine were included,and the proportion of males was higher than that of females,and middle-aged and elderly people were the most common group.A total of 2170 prescriptions of traditional Chinese medicine were included,involving a total of 383 traditional Chinese medicines.High-frequency medicines included poria,Radix Bupleuri,Radix Scutellariae,Herba Pogostemonis,Fructus Forsythiae,Flos Loniceraeetc.The four natures were mainly concentrated in cold,warm and neutral,and the five flavors were mainly concentrated in bitter,pungent and sweet.The herbal medicines were mainly attributed to the lungs and stomach meridians,and were mainly of heat-clearing,exterior syndrome-relieving and diuresis-promoting and damp-clearing types.A total of 24 high-frequency herbal combinations and 35 association rule were excavated,and 3 types of formulas were obtained by cluster analysis.[Conclusions]The analysis results and medicine combinations obtained in the formulas are consistent with the traditional Chinese medicine treatment theory of COVID-19 caused by wind-heat filth accompanied with damp and toxin.

Metabolic complications of psychotropic medications in psychiatric disorders:Emerging role of de novo lipogenesis and therapeutic consideration

Although significant advances have been made in understanding the pathophysiology of psychiatric disorders(PDs),therapeutic advances have not been very convincing.While psychotropic medications can reduce classical symptoms in patients with PDs,their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes,obesity and non-alcoholic fatty liver disease(NAFLD).The mechanism(s)underlying these metabolic abnormalities is not clear;however,lipid/fatty acid accumulation due to enhanced de novo lipogenesis(DNL)has been shown to reduce membrane fluidity,increase oxidative stress and inflammation leading to the development of the aforementioned metabolic abnormalities.Intriguingly,emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity,diabetes and NAFLD after long-term treatment with psychotropic medications in patients with PDs.In support of this,several adjunctive drugs comprising of anti-oxidants and antiinflammatory agents,that are used in treating PDs in combination with psychotropic medications,have been shown to reduce insulin resistance and development of NAFLD.In conclusion,the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities,and a new avenue for translational research and therapeutic drug designing in PDs.

Tumor infiltrating lymphocytes in gastric cancer:Unraveling complex interactions for precision medicine

This editorial will focus on tumor immunity and the factors that alter the tumor immune micro-environment.The role of tumor infiltrating lymphocytes(TILs)will also be discussed in detail,including the types,mechanism of action,and role.Gastric cancer(GC)often presents in the advanced stage and has various factors predicting the outcomes.The interplay of these factors and their correlation with the TILs is discussed.A literature review revealed high intratumoral TILs associated with higher grade,HER2-,and Helicobacter pylori negativity.Moreover,stromal(ST)TILs correlated with lower grade and lesser recurrence risk in GC.High TILs in ST and invasive border also correlated with mismatch repair deficiency status.Further characterization of the CD3+,CD8+,and other cells is also warranted.In the future,this complex correlation of cancer cells with the immune system can be explored for therapeutic avenues.

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment planning.Liver Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and challenging.This review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and resilience.Performance metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical contexts.The review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging conditions.It suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular methods.This paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

Analysis of the Effect of Family-Centered Empowerment Model(FCEM)Health Education Through WeChat on Medication Compliance and Blood Pressure of Elderly Hypertensive Patients in Rural Areas

Objective: To validate the effectiveness of a Family-Centered Empowerment Model (FCEM) health education through WeChat on medication compliance and blood pressure among elderly hypertensive patients in rural areas. Methods: One hundred and two rural elderly hypertensive patients aged 65-80 years were selected and randomly divided into an experimental and control group of 51 each. The control group implemented conventional health education, and the experimental group implemented FCEM health education through WeChat platform for 4 consecutive weeks. The Therapeutic Adherence Scale for Hypertensive Patients (TASHP) scores and blood pressure measurements were compared between and within the two groups. Results: After the intervention, there were significant differences in medication compliance and blood pressure between the two groups (P < 0.001). In the control group, before and after the intervention, there was a significant difference in medication compliance (P < 0.001), but no significant difference in blood pressure (P > 0.05). In the experimental group, there were significant differences in medication compliance and blood pressure before and after the intervention (P < 0.001). Conclusion: The FCEM health education through an online social platform significantly improved medication compliance and led to effective blood pressure control in rural elderly hypertensive patients. Therefore, as an effective, safe, and economical model, it is also necessary to explore its effectiveness in improving health problems in other chronic diseases and other age groups.

Medical imaging-based companion diagnostics for solid tumors

Heterogeneity within the solid tumor microenvironment contributes to a poor prognosis and limited therapeutic responses.Companion diagnostics(CDx),a clinical technique that gives doctors vital biomarker information to enhance patient outcomes through matching specific treatments to patients,is becoming more and more important.However,most current US Food and Drug Administration(FDA)-approved CDx tests have difficulty dynamically reflecting variations in biomarkers in the solid tumor microenvironment because they are used in vitro and ex vivo.Consequently,new medical imaging-based CDx tests have been widely used to detect interpatient and intrapatient tumor heterogeneity to assess the intratumoral distribution of specific biomarkers and microenvironment variables.They provide patient stratification for targeted therapies and the differentiation of patient populations that benefit from alternative treatments.This review provides an overview of the recent advances in medical imaging-based CDx for solid tumors and summarizes the various tumor microenvironment biomarkers utilized in imaging-based CDx.We believe that this review offers additional details and directions for promoting medical imaging-based CDx development.

The breast cancer tumor microenvironment and precision medicine:immunogenicity and conditions favoring response to immunotherapy

Some main recent researches that have dissected tumor microenvironment(TME)by imaging mass cytometry(IMC)in different subtypes of primary breast cancer samples were considered.The many phenotypic variants,clusters of epithelial tumor and immune cells,their structural features as well as the main genetic aberrations,sub-clonal heterogeneity and their systematic classification also have been examined.Mutational evolution has been assessed in primary and metastatic breast cancer samples.Overall,based on these findings the current concept of precision medicine is questioned and challenged by alternative therapeutic strategies.In the last two decades,immunotherapy as a powerful and harmless tool to fight cancer has received huge attention.Thus,the tumor immune microenvironment(TIME)composition,its prognostic role for clinical course as well as a novel definition of immunogenicity in breast cancer are proposed.Investigational clinical trials carried out by us and other findings suggest that G0-G1 state induced in endocrine-dependent metastatic breast cancer is more suitable for successful immune manipulation.Residual micro-metastatic disease seems to be another specific condition that can significantly favor the immune response in breast and other solid tumors.

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for diagnosis.The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification.Most of the extracted image features are irrelevant and lead to an increase in computation time.Therefore,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features.This process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel distributions.The similarity between the pixels over the various distribution patterns with high indexes is recommended for disease diagnosis.Later,the correlation based on intensity and distribution is analyzed to improve the feature selection congruency.Therefore,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the distribution.Now,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of selection.Therefore,the probability of feature selection,regardless of the textures and medical image patterns,is improved.This process enhances the performance of ML applications for different medical image processing.The proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected dataset.The mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.