CP-AnemiC:A conjunctival pallor dataset and benchmark for anemia detection in children

Anemia is a universal public health issue,which occurs as the result of a reduction in red blood cells.This disease is common among children in Africa and other developing countries.If not treated early,children may suffer longterm consequences such as impairment in social,emotional,and cognitive functioning.Early detection of anemia in children is highly desirable for effective treatment measures.While there has been research into the development of computer-aided diagnosis(CAD)systems for anemia diagnosis,a significant proportion of these studies encountered limitations when working with limited datasets.To overcome the existing issues,this paper proposes a large dataset,named CP-AnemiC,comprising 710 individuals(range of age,6–59 months),gathered from several hospitals in Ghana.The conjunctiva image-based dataset is supported with Hb levels(g/dL)annotations for accurate diagnosis of anemia.A joint deep neural network is developed that simultaneously classifies anemia and estimates hemoglobin levels(g/dL)based on the conjunctival pallor images.This paper conducts a comprehensive experiment on the CP-AnemiC dataset.The experimental results demonstrate the efficacy of the joint deep neural network in both the tasks of anemia classification and Hb levels(g/dL)estimation.

Detection of anemia using conjunctiva images:A smartphone application approach

Anemia is one of the public health issues that affect children and pregnant women globally.Anemia occurs when the level of red blood cells within the body is reduced.Detecting anemia requires expert blood draw for clinical analysis of hemoglobin quantity.Although this standard method is accurate,it is costive and consumes enough time,unlike the non-invasive approach which is cost-effective and takes less time.This study focused on pallor analysis and used images of the conjunctiva of the eyes to detect anemia using machine learning techniques.This study used a publicly available dataset of 710 images of the conjunctiva of the eyes acquired with a unique tool that eliminates any interference from ambient light.We combined Convolutional Neural Networks,Logistic Regression,and Gaussian Blur algorithm to develop a conjunctiva detection model and an anemia detection model which runs on a Fast API server connected to a frontend mobile app built with React Native.The developed model was embedded into a smartphone application that can detect anemia by capturing and processing a patient's conjunctiva with a sensitivity of 90%,a specificity of 95%,and an accuracy of 92.50%on average performance in about 50 s.

Effect of ultrasound with methylene blue as sound sensitive agent on virus inactivation

The goal of this paper is to explore a method for virus inactivation based on ultrasonic treatment,and on this basis,to explore the synergistic effect of methylene blue as a sonosensitizer in virus inactivation.The titer of human parainfluenza virus type 3(HPIV3),Autographacaliforinica nuclear polyhedrosis virus carried a green fluorescent reporter gene(AcNPV-GFP)and Enterovirus group D 68(EV-D68)were determined by plaque assays or TCID50 methods after treatment by MB combined with illumination(MB photochemical,MBP)or ultrasonic excitation.Different ultrasonic power and time,MB concentration gradient were set to determine the best antiviral combination.For the enveloped virus HPIV3 and AcNPV-GFP,pure ultrasonic or MBP treatment could reduce viral titer more than 104,and ultrasonic combined with MB could completely inactivate HPIV3 and AcNPV-GFP in 5min while traditional MBP methods could only reduce viral titer about 10X.For the nonenveloped virus EV-D68,pure ultrasonic or MBP treatment only reduced the viral titer about 102,but ultrasonic combined with MB treatment could reduce the viral titer about 103 in 5min and completely inactive EV-D68 in 10min(reduced 105).Compared with MBP method and pure ultrasonic inactivation,ultrasonic combined with MB has better inactivation effect on either enveloped or non-enveloped viruses,and the appropriate combination of parameters is expected to be a new blood transfusion transmitted virus inactivation method.

Identifying potential compounds from Bacopa monnieri(brahmi)against coxsackievirus A16 RdRp targeting HFM disease(tomato flu)

Hand,foot,and mouth disease(HFMD),primarily instigated by Coxsackievirus A16(CVA16),poses a serious health concern,necessitating effective therapeutic interventions.The RNA-dependent RNA polymerase(RdRp)of CVA16 emerges as a promising drug target for HFMD treatment.This study presents an in-silico pipeline for the identification of potential RdRp inhibitors against CVA16.A library of 91 natural compounds derived from Bacopa monnieri(brahmi)was virtually screened against the CVA16 RdRp.Here,Bacobitacin D emerged as a promising hit molecule,forming 8 hydrogen bonds including key catalytic site residues(Asp^(238)and Asp^(329))within the RdRp active site.Further,molecular dynamics(MD)simulations and MM/GBSA binding free energy calculations was applied on the top three hits that were selected based on exhaustive docking scores(≤-9.55 kcal/mol).Bacobitacin D exhibited sustainable stability,as evidenced by minimal deviation(RMSD=0.75±0.02 nm)during a 100 ns MD simulation.Importantly,Bacopaside IV exhibited the lowestΔGTOTAL binding free energy(-23.70 kcal/mol),while Bacobitacin D displayed a comparableΔGTOTAL of19.14 kcal/mol.Structural interpretation of the most populated cluster derived from MD simulations showed direct interactions of Bacobitacin D with pivotal catalytic residues,including Asp^(238)and Ser^(289).This comprehensive study confirmed Bacobitacin D as a potent inhibitor of CVA16 RdRp,offering a potential avenue for therapeutic intervention against HFMD.Experimental validation is required to confirm the inhibitory action of Bacobitacin D against HFMD.

Effective techniques and emerging alternatives in orthodontic tooth movement:A systematic review

Orthodontic procedures can be inconvenient in nature.To overcome this problem,accelerated orthodontics play a very important role to reduce existing trouble and discomfort.The most common inconvenience caused during orthodontic treatment procedures is that they are very time consuming which can result in several drawbacks,including an increased risk of tooth decay,gingival recession,and root resorption.Various methods can be employed to expedite orthodontic treatment by accelerating tooth movement,including surgical-assisted procedures,biological interventions,and the utilization of devices.These approaches effectively reduce the overall period of treatment.The purpose of this review is to study the effective techniques for orthodontic tooth movement as well as highlight various orthodontic accelerating methods in the respective approaches.Some nonsurgical studies indicated that drug-induced methods can have a therapeutic effect on tooth movement.One of the approaches involves the local administration of Vitamin 1.25D,which has been found to expedite tooth movement.Vibrational orthodontic devices are a painless and cost-effective option that is considered the least invasive approach for accelerating tooth movement.Meanwhile,surgical approach is also a successful method,wherein great results and strong PDL tissue response were observed,but they cause a lot of pain and discomfort to the patient.Therefore,due to the strengths and limitations of each procedure covered in the study,more research should be done to identify the fastest way to speed up tooth mobility。

Numerical analysis of hemodynamic parameters in stenosed arteries under pulsatile flow conditions

This research studies the changes in flow patterns and hemodynamic parameters of diverse shapes and sizes of stenosis.Six different shapes and sizes of stenosis are constructed to investigate the variations in hemodynamics as the morphology changes.Changes in shape(trapezoidal and bell-shaped)and sizes of stenosis change the stresses on the walls and their flow patterns.TAWSS and OSI results specify that trapezoidal stenosis exerts greater stress than bell-shaped stenosis.Also,as the length of the trapezoidal stenosis increases,the TAWSS increases,whereas the trend is the opposite for bell-shaped stenosis.Later,this paper also studies different degrees of stenosis extracted from real images.Changes in velocity flow patterns,wall shear stress(WSS),Time-averaged wall shear stress(TAWSS)and Oscillatory shear index(OSI)have been studied for these images.Results illustrate that the peak velocity rises drastically as the stenosis percentage increases.Negative velocity is seen close to the artery's walls,indicating flow separation.This flow separation region is seen throughout the cycle except in the accelerating flow region.An increase in stenosis also increases WSS and TAWSS drastically.Negative WSS is seen downstream of stenosis,indicating flow recirculation.Such negative WSS in the blood vessels also promotes endothelial dysfunction.OSI values greater than 0.2 are seen near the stenosis region,indicating atherosclerosis growth.Regions of high OSI and low TAWSS are also identified,indicating probable regions of plaque development.

Enhancing Parkinson's disease severity assessment through voice-based wavelet scattering,optimized model selection,and weighted majority voting

Parkinson's disease(PD)is a neurodegenerative disorder characterized by motor and non-motor symptoms that significantly impact an individual's quality of life.Voice changes have shown promise as early indicators of PD,making voice analysis a valuable tool for early detection and intervention.This study aims to assess and detect the severity of PD through voice analysis using the mobile device voice recordings dataset.The dataset consisted of recordings from PD patients at different stages of the disease and healthy control subjects.A novel approach was employed,incorporating a voice activity detection algorithm for speech segmentation and the wavelet scattering transform for feature extraction.A Bayesian optimization technique is used to fine-tune the hyperparameters of seven commonly used classifiers and optimize the performance of machine learning classifiers for PD severity detection.AdaBoost and K-nearest neighbor consistently demonstrated superior performance across various evaluation metrics among the classifiers.Furthermore,a weighted majority voting(WMV)technique is implemented,leveraging the predictions of multiple models to achieve a near-perfect accuracy of 98.62%,improving classification accuracy.The results highlight the promising potential of voice analysis in PD diagnosis and monitoring.Integrating advanced signal processing techniques and machine learning models provides reliable and accessible tools for PD assessment,facilitating early intervention and improving patient outcomes.This study contributes to the field by demonstrating the effectiveness of the proposed methodology and the significant role of WMV in enhancing classification accuracy for PD severity detection.

Material,design,and fabrication of custom prosthetic liners for lower-extremity amputees:A review

As a physical interface,a prosthetic liner is commonly used as a transition material between the residual limb and the stiff socket.Typically made from a compliant material such as silicone,the main function of a prosthetic liner is to protect the residual limb from injuries induced by load-bearing normal and shear stresses.Compared to conventional liners,custom prosthetic lower-extremity(LE)liners have been shown to better relieve stress concentrations in painful and sensitive regions of the residual limb.Although custom LE liners have been shown to offer clinical benefits,no review article on their design and efficacy has yet been written.To address this shortcoming in the literature,this paper provides a comprehensive survey of custom LE liner materials,design,and fabrication methods.First,custom LE liner materials and components are summarized,including a description of commercial liners and their efficacy.Subsequently,digital methods used to design and fabricate custom LE liners are addressed,including residual limb biomechanical modeling,finite element-based design methods,and 3-D printing techniques.Finally,current evaluation methods of custom/commercial LE liners are presented and discussed.We hope that this review article will inspire further research and development into the design and manufacture of custom LE liners.

Review of biomechanical deviations among nonpregnant,pregnant,and postpartum cohorts

During pregnancy,women experience substantial changes in physiology,morphology,and hormonal systems.These changes have profound effects on the biomechanics of the human body,particularly the musculoskeletal system,resulting in discomfort,pain,and decreased body stability.Sufficient biomechanical knowledge is critical for understanding the etiology and precautions of musculoskeletal disorders.With awareness of health problems in the pregnant cohort,identification,intervention,and precaution of problems have garnered attention.Researchers have conducted studies to determine the biomechanics of pregnancy.There have been review studies on summarization.However,to the best of our knowledge,few studies have comprehensively described biomechanical changes throughout pre-,in-,and postpartum periods.This review analyzed available studies on biomechanical changes during these three periods in the electronic databases of PubMed,Scopus,and Cochrane from inception until June 2,2021.Synthesized the general information,age of the studied subjects,investigated periods,sample size,objectives,measurement tools,and outcomes of reviewed studies.And Using National Institutes of Health quality assessment tool for observational cohort and cross-sectional studies to assessment the quality of the reviewed articles.These studies revealed biomechanical deviations in body stability,motion patterns,and gait modes during these three periods.Regarding research content,there are insufficient studies on certain critical biomechanical aspects,such as the kinetic parameters of the inner body,which are the most direct factors related to musculoskeletal problems.According to the National Institutes of Health quality assessment tool for observational cohort and cross-sectional studies,a more comprehensive and explicit understanding of pregnancy biomechanics can be expected.

Acupuncture for treating adolescent depression:Study protocol for a randomized controlled trial

The prevalence of depression among adolescents has been significantly increasing in recent years.However,current antidepressants for adolescents have limited safety and efficacy.Acupuncture has been shown to be effective in treating depression in adults,but there is a lack of high-quality evidence for its effect on the treatment of adolescent depression,and the underlying mechanism is still unclear.Therefore,we designed a randomized controlled trial to explore the effectiveness and the therapeutic mechanisms of acupuncture on adolescent depression.This study will be designed as a multi-center,sham and randomized controlled clinical trial.For this purpose,a total of 96 adolescent depression patients diagnosed with moderate and severe depression will be randomly divided into the manual acupuncture group and the sham one,respectively.The two groups received acupuncture treatment 3 times a week for a total course lasting 4 weeks.All patients will be assessed according to the primary outcomes including Beck Depression Inventory-II(BDI-II),Hamilton Depression Rating Scale(HAMD-24)and Zung self-rating depression scale(SDS)at baseline,week 2,4 and 8.Additionally,the secondary outcomes will be assessed at baseline and week 4,which includes intestinal flora structure,fecal short chain fatty acids(SCFAs)content and serum serotonin(5-HT)level.This study is the first randomized trial of acupuncture treatment of adolescent depression.

Recent advances in alginate based gastroretentive technologies for drug delivery applications

The efficacy of orally delivered medicines can be maximized through enhancing the gastric residence period and modifying the drug release pattern according to therapeutic need.Several technologies were investigated through recent years for increasing gastric retention of medicines.Biopolymers are one of the widely studied materials for increasing the retention of drug delivery systems in the stomach region.The biodegradability,biocompatibility and non-toxic behavior in combination with the easy fabrication technologies has made biopolymers an interesting option to pharmaceutical scientists for developing gastroretentive drug delivery systems(GRDDS).Several gastroretentive approaches are reported to be efficacious to localize the drug delivery system in the gastric region.Alginates are commonly employed polysaccharide for developing various GRDDS including low density systems,mucoadhesive systems,swellable systems,hydrogel forming systems,in situ gelling systems,raft forming systems,magnetic systems.The abundant availability from marine and bacterial sources in combination with its attractive physicochemical nature has encouraged pharmaceutical researchers to investigate its suitability in developing various drug delivery system.The mucoadhesive,hydrogel forming and raft forming behavior of alginates makes alginate suitable for GRDDS.The attractive properties of alginate makes it a useful biopolymer in the biomedical field.This review focuses on the source and chemistry of alginates and describes the applications of alginates in developing novel gastroretentive drug delivery systems.

Deep learning based detection of monkeypox virus using skin lesion images

As we set into the second half of 2022,the world is still recovering from the two-year COVID-19 pandemic.However,over the past three months,the outbreak of the Monkeypox Virus(MPV)has led to fifty-two thousand confirmed cases and over one hundred deaths.This caused the World Health Organisation to declare the outbreak a Public Health Emergency of International Concern(PHEIC).If this outbreak worsens,we could be looking at the Monkeypox virus causing the next global pandemic.As Monkeypox affects the human skin,the symptoms can be captured with regular imaging.Large samples of these images can be used as a training dataset for machine learning-based detection tools.Using a regular camera to capture the skin image of the infected person and running it against computer vision models is beneficial.In this research,we use deep learning to diagnose monkeypox from skin lesion images.Using a publicly available dataset,we tested the dataset on five pre-trained deep neural networks:GoogLeNet,Places365-GoogLeNet,SqueezeNet,AlexNet and ResNet-18.Hyperparameter was done to choose the best parameters.Performance metrics such as accuracy,precision,recall,f1-score and AUC were considered.Among the above models,ResNet18 was able to obtain the highest accuracy of 99.49%.The modified models obtained validation accuracies above 95%.The results prove that deep learning models such as the proposed model based on ResNet-18 can be deployed and can be crucial in battling the monkeypox virus.Since the used networks are optimized for efficiency,they can be used on performance limited devices such as smartphones with cameras.The addition of explainable artificial intelligence techniques LIME and GradCAM enables visual interpretation of the prediction made,helping health professionals using the model.

The applications of wearable devices in the rehabilitation of ankle injuries: A systematic review and meta-analysis

Wearable devices have been used in the treatment and rehabilitation of ankle injuries.This article systematically reviewed the trials that summarize and evaluate the effectiveness of rehabilitation treatment after an ankle injury.Three databases,PubMed(1974–2021),Embase,and Web of Science(1950–2021),were searched.The intervention was any wearable device,and the outcome measures were Activities Scale for Kids performance(ASKp),Foot and Ankle Outcome Score(FAOS),American Orthopaedic Foot and Ankle Society(AOFAS),Olerud-Molander Ankle Score(OMAS),and Circumference as measured by any validated outcome measure.Two independent authors evaluated the studies with the Cochrane risk-of-bias tool.Four papers were included,involving 476 participants,with a mean age of 29.3±6.7 years.The mean duration of wearable devices was 3.83 weeks,and the mean length of training was 3.75 weeks.Wearable devices achieved better results compared with control on the functional performance(standardized mean difference[SMD]0.66;95%confidence interval[CI]0.29 to 1.04;I^(2)=76%;P<0.001),as well as ankle score(SMD 0.78;95%CI 0.22 to 1.35;I^(2)=82%;P<0.001).The definitive judgment could not be made due to the variability in training,training duration,and outcomes measurement.Wearable devices are a promising approach that has positive effects on ankle injuries in terms of functional performance and reducing the extent of swelling.There is insufficient evidence from randomized controlled trials(RCTs)to support this for ankle injury patients using wearable devices.Therefore,there is an need for well-conducted randomized controlled trials investigating more adaptive orthoses to achieve more effective strategies for early functional rehabilitation.PROSPERO registration number:CRD42021246289.

An experimental investigation on pulse transit time and pulse arrival time using ecg, pressure and ppg sensors

Pulse transit time(PTT)and pulse arrival time(PAT)are explored using multiple sensors connected to the human body.Pulse wave velocity(PWV)is indirectly computed using PTT.We conducted a study using ECG,Pressure,and PPG sensor to capture the PAT and PTT information noninvasively.Three PAT and three PTT values were obtained from the body.An electrocardiograph(ECG/EKG)is used as a reference signal for three PAT values.PTT values were obtained using pressure and PPG sensors connected at the wrist and fingertip respectively.A pressure sensor module was constructed to measure PTT at the wrist and the results were compared with the other standard reference values.Heart rate variability was found to be relatively lower in both ECG and PPG sensors as compared with pressure sensors at the wrist.The PAT obtained from ECG and PPG sensor was found to have the least variation of 0:386±0:037 sec with 9.58% of the variation.PTT at the wrist captured using a pressure sensor was recorded to be 0:026±0:013 sec with 50% of the variation.PTT values measured using ECG and pressure sensor were found to be correlating with ECG and PPG.The experimental result indicates different ranges of the PWV which indicates that the flow velocity of the blood varies with different arteries.PTT can be effectively computed from pressure and PPG sensors,and this makes it possible to extract different pulse features in the wearable devices without the need of ECG signal or PAT as reference.

Design of polysaccharide gum based network copolymeric hydrogels for drug delivery and wound dressing applications

This article deals with the exploration of the design of network crosslinked structure by covalent bonding for use as wound dressing materials keeping in view inherent therapeutic role of neem gum in wound healing.These copolymeric hydrogels were prepared by graft-copolymerization reaction of carbopol and poly(N-vinylpyrrolidone)(poly(NVP).Antibiotic drug levofloxacin was encapsulated in dressings for better wound healing.The scanning electron microscopy(SEM),atomic force microscopy(AFM),Fourier transform infrared(FTIR)spectroscopy,^(13)C nuclear magnetic resonance(NMR)spectroscopy,X-ray diffraction(XRD),thermogravimetric analysis(TGA),differential thermal gravimetry(DTG),and differential scanning calorimetry(DSC)techniques were applied for characterization.NMR and FTIR demonstrated incorporation of carbapol and poly(NVP)in dressings.XRD indicated amorphous state in copolymeric dressings.Interactions of copolymers with drug,blood and bio membrane were studied to evaluate biomedical properties which revealed controlled release of drug from hydrogel dressings which were possessing blood-compatible(haemolytic value=2.4±0.82)and mucoadhesive(detachment force=124±41 mN)properties.Dressings were permeable to O2 and H2O vapour and absorbed 6.68±±0.62 g/g wound fluid which is ideal dressing characteristic.Diffusion mechanism type of drug levofloxacin was Fickian with kinetic model First order.These properties suggested use of hydrogel material for wound dressing and drug delivery applications for better wound care management.This article deals with the exploration of the design of network crosslinked structure by covalent bonding for use as wound dressing materials keeping in view inherent therapeutic role of neem gum in wound healing.These copolymeric hydrogels were prepared by graft-copolymerization reaction of carbopol and poly(N-vinylpyrrolidone)(poly(NVP).Antibiotic drug levofloxacin was encapsulated in dressings for better wound healing.The scanning electron microscopy(SEM),atomic force microscopy(AFM),Fourier transform infrared(FTIR)spectroscopy,13C nuclear magnetic resonance(NMR)spectroscopy,X-ray diffraction(XRD),thermogravimetric analysis(TGA),differential thermal gravimetry(DTG),and differential scanning calorimetry(DSC)techniques were applied for characterization.NMR and FTIR demonstrated incorporation of carbapol and poly(NVP)in dressings.XRD indicated amorphous state in copolymeric dressings.Interactions of copolymers with drug,blood and bio membrane were studied to evaluate biomedical properties which revealed controlled release of drug from hydrogel dressings which were possessing blood-compatible(haemolytic value=2.45±.82)and mucoadhesive(detachment force=124±41 mN)properties.Dressings were permeable to O2 and H_(2)O vapour and absorbed 6.68±0.62 g/g wound fluid which is ideal dressing characteristic.Diffusion mechanism type of drug levofloxacin was Fickian with kinetic model First order.These properties suggested use of hydrogel material for wound dressing and drug delivery applications for better wound care management.

The sound of blood:photoacoustic imaging in blood analysis

Blood analysis is a ubiquitous and critical aspect of modern medicine.Analyzing blood samples requires invasive techniques,various testing systems,and samples are limited to relatively small volumes.Photoacoustic imaging(PAI)is a novel imaging modality that utilizes non-ionizing energy that shows promise as an alternative to current methods.This paper seeks to review current applications of PAI in blood analysis for clinical use.Furthermore,we discuss obstacles to implementation and future directions to overcome these challenges.Firstly,we discuss three applications to cellular analysis of blood:sickle cell,bacteria,and circulating tumor cell detection.We then discuss applications to the analysis of blood plasma,including glucose detection and anticoagulation quantification.As such,we hope this article will serve as inspiration for PAI's potential application in blood analysis and prompt further studies to ultimately implement PAI into clinical practice.

Effect of 3D anchorage attachment on the alleviating tipping/extrusion of premolars for en-mass distalization of maxillary molars with clear aligners:A finite element study

This study aimed to explore the optimal invisible orthodontic force system during the en-mass distalization of two maxillary molars to minimize the side effect of anchorage loss by changing the direction of the application of the orthodontic force system.A high bio-fidelity 3D finite element model including maxilla,periodontal ligament,dentition,clear aligner,3D anchorage attachment and mini-implant was established.Different lengths of lateral hooks of 3D-printed anchorage attachments and mini-implant positions into the palatal alveolus were considered.A 200 g distal force was applied to the lateral hooks of different horizontal lengths(3.26 mm,6.52 mm and 9.78 mm)with the mini-implant as the application point.Using ABAQUS software,orthodontic tooth movements under 12 different clinical treatment designs were analyzed and calculated.The 3D anchorage attachment enhanced the anchorage of anterior teeth and alleviated the tipping/extrusion of premolars.In contrast to without clear aligners,length of the lateral hook had a negligible effect on both mesial tipping and buccal tipping with clear aligners,which could then be ignored.The change in mesial tipping was less and nearly remained constant despite of the different heights of the mini-implant.The 3D anchorage attachment assisted clear aligner can avoid the side effects of anterior tooth proclination caused by insufficient anchorage.The length of the lateral hook,and height of the mini-implant in this invisible orthodontic force system hardly affects the tooth movement of anchorage units.Clear aligners can effectively control the rotation and tipping of anchorage units caused by 3D anchorage attachment.

A computer vision-approach for activity recognition and residential monitoring of elderly people

In this study,we explore a human activity recognition(HAR)system using computer vision for assisted living systems(ALS).Most existing HAR systems are implemented using wired or wireless sensor networks.These systems have limitations such as cost,power issues,weight,and the inability of the elderly to wear and carry them comfortably.These issues could be overcome by a computer vision based HAR system.But such systems require a highly memory-consuming image dataset.Training such a dataset takes a long time.The proposed computervision-based system overcomes the shortcomings of existing systems.The authors have used key-joint angles,distances between the key joints,and slopes between the key joints to create a numerical dataset instead of an image dataset.All these parameters in the dataset are recorded via real-time event simulation.The data set has 780,000 calculated feature values from 20,000 images.This dataset is used to train and detect five different human postures.These are sitting,standing,walking,lying,and falling.The implementation encompasses four distinct algorithms:the decision tree(DT),random forest(RF),support vector machine(SVM),and an ensemble approach.Remarkably,the ensemble technique exhibited exceptional performance metrics with 99%accuracy,98%precision,97%recall,and an F1 score of 99%.

Effect of the antenna slot numbers and position on the performance of microwave ablation

Microwave ablation(MWA)is a type of thermal ablation used for cancer treatment in interventional radiology.To induce localized tissue heating MWA employs electromagnetic waves within the microwave energy spectrum,which is done by the precisely designed antenna.This study substantially emphasizes the design and performance ameliorating of slot(both single and double)antennae and compares the results with conventional monopole antennae in terms of temperature distribution,specific absorption ratio(SAR),and thermal tissue damage rate.The simulation has been done in COMSOL by solving the Bioheat equation along with Maxwell electromagnetic equations using the finite element method.The simulation results reveal that the double-slot antenna has the most accurate and directional heat dissipation for liver tumors as well as the highest tissue damage rate and SAR.The highest SAR was found to be 3500 W/kg and 3350 W/kg at the implant depth of 61 mm and 63 mm for double and single-slot antennae,respectively.In addition,the fastest tissue damage occurred near the upper slot of the double-slot antenna.This study helps to understand the basic design parameters for enhancing single and doubleslot antennae performance.

3D pulmonary vessel segmentation based on improved residual attention u-net

Automatic segmentation of pulmonary vessels is a fundamental and essential task for the diagnosis of various pulmonary vessels diseases.The accuracy of segmentation is suffering from the complex vascular structure.In this paper,an Improved Residual Attention U-Net(IRAU-Net)aiming to segment pulmonary vessel in 3D is proposed.To extract more vessel structure information,the Squeeze and Excitation(SE)block is embedded in the down sampling stage.And in the up sampling stage,the global attention module(GAM)is used to capture target features in both high and low levels.These two stages are connected by Atrous Spatial Pyramid Pooling(ASPP)which can sample in various receptive fields with a low computational cost.By the evaluation experiment,the better performance of IRAU-Net on the segmentation of terminal vessel is indicated.It is expected to provide robust support for clinical diagnosis and treatment.