Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

Computed tomography enterography-based radiomics for assessing mucosal healing in patients with small bowel Crohn's disease

BACKGROUND Mucosal healing(MH)is the major therapeutic target for Crohn's disease(CD).As the most commonly involved intestinal segment,small bowel(SB)assessment is crucial for CD patients.Yet,it poses a significant challenge due to its limited accessibility through conventional endoscopic methods.AIM To establish a noninvasive radiomic model based on computed tomography enterography(CTE)for MH assessment in SBCD patients.METHODS Seventy-three patients diagnosed with SBCD were included and divided into a training cohort(n=55)and a test cohort(n=18).Radiomic features were obtained from CTE images to establish a radiomic model.Patient demographics were analysed to establish a clinical model.A radiomic-clinical nomogram was constructed by combining significant clinical and radiomic features.The diagnostic efficacy and clinical benefit were evaluated via receiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA),respectively.RESULTS Of the 73 patients enrolled,25 patients achieved MH.The radiomic-clinical nomogram had an area under the ROC curve of 0.961(95%confidence interval:0.886-1.000)in the training cohort and 0.958(0.877-1.000)in the test cohort and provided superior clinical benefit to either the clinical or radiomic models alone,as demonstrated by DCA.CONCLUSION These results indicate that the CTE-based radiomic-clinical nomogram is a promising imaging biomarker for MH and serves as a potential noninvasive alternative to enteroscopy for MH assessment in SBCD patients.

Rethinking the diagnosis and treatment of renal anastomotic hemangioma after partial nephrectomy

Renal anastomotic hemangioma(AH)is a rare,benign vascular tumor with unique histopathological features,a disease that is clinically rare,and existing clinical cases offer different treatment options.As reported in the text,this is a very unusual case of renal AH with AH secondary to residual renal tissue after renal clear cell carcinoma,describing a rare renal AH and a history of renal clear cell carcinoma,including ultrasound,computed tomography and magnetic re-sonance imaging.However,the available imaging data and the literature do not provide an effective basis for the diagnosis of the disease,raising the lack of un-derstanding and misdiagnosis,where the patient eventually underwent neph-rectomy,but the author is not the most appropriate surgical treatment.The po-stoperative pathological results of the patient are benign lesions,and it is unde-niable that nephrectomy is suspected to be overtreated.By reading the literature,we provide different insights into the treatment of the patient,and we hope that this paper can provide some help for the future clinical diagnosis and treatment.

Internal hernia as a rare cause of small bowel obstruction:An insight from 13 years of experience

BACKGROUND Internal hernia(IH)is a rare culprit of small bowel obstruction(SBO)with an incidence of<1%.It poses a considerable diagnostic challenge requiring a high index of suspicion to prevent misdiagnosis,improper treatment,and subsequent morbidity and mortality.AIM To determine the clinico-demographic profile,radiological and operative findings,and postoperative course of patients with IH and its association with SBO.METHODS Medical records of 586 patients with features of SBO presenting at a tertiary care centre at Lucknow,India between September 2010 and August 2023 were reviewed.RESULTS Out of 586 patients,7(1.2%)were diagnosed with IH.Among these,4 had congenital IH and 3 had acquired IH.The male-to-female ratio was 4:3.The median age at presentation was 32 years.Contrast-enhanced computed tomography(CECT)was the most reliable investigation for preoperative identification,demonstrating mesenteric whirling and clumped-up bowel loops.Left paraduodenal hernia and transmesenteric hernia occurred with an equal frequency(approximately 43%each).Intraoperatively,one patient was found to have bowel ischemia and one had associated malrotation of gut.During follow-up,no recurrences were reported.CONCLUSION IH,being a rare cause,must be considered as a differential diagnosis for SBO,especially in young patients in their 30s or with unexplained abdominal pain or discomfort post-surgery.A rapid imaging evaluation,preferably with CECT,is necessary to aid in an early diagnosis and prompt intervention,thereby reducing financial burden related to unnecessary investigations and preventing the morbidity and mortality associated with closed-loop obstruction and strangulation of the bowel.

Primary parenchymal squamous cell carcinoma of the kidney:A case report

BACKGROUND Primary squamous cell carcinoma(SCC)of the renal parenchyma is extremely rare,with only nine cases reported.CASE SUMMARY This study reports a 51-year-old man with primary SCC of the renal parenchyma.The patient was admitted with recurrent dull pain and discomfort in the right lumbar region,which had worsened over 2 weeks,accompanied by painful gross hematuria.SCC antigen(SCCA)levels were elevated,and imaging revealed a renal mass with associated calculi.The patient underwent laparoscopic unilateral nephrectomy and lymph node dissection.Postoperative pathology confirmed highly differentiated SCC with necrosis in the right renal parenchyma,with negative renal pelvis and ureter.The pathological stage was Pt3aN1M0.Four months after surgery,the tumor recurred with involvement of the liver,right psoas major muscle,and inferior vena cava.The patient refused chemotherapy and succumbed to the disease 6 months postoperatively due to disease progression.CONCLUSION We report a case of primary SCC of the renal parenchyma,a rare renal malignancy.The clinical symptoms,laboratory tests,and imaging findings are nonspecific,making accurate and timely diagnosis challenging.According to the literature,for patients with renal calculi accompanied by a renal mass,elevated serum SCCA levels,and magnetic resonance imaging showing cystic or cystic-solid masses within the kidney with pseudocapsules and heterogeneous mild enhancement,the possibility of this disease should be considered.

Radiomics and molecular analysis:Bridging the gap for predicting hepatocellular carcinoma prognosis

This editorial examines a recent study that used radiomics based on computed tomography(CT)to predict the expression of the fibroblast-related gene enhancer of zeste homolog 2(EZH2)and its correlation with the survival of patients with hepatocellular carcinoma(HCC).By integrating radiomics with molecular analysis,the study presented a strategy for accurately predicting the expression of EZH2 from CT scans.The findings demonstrated a strong link between the radiomics model,EZH2 expression,and patient prognosis.This noninvasive approach provides valuable insights into the therapeutic management of HCC.

Pulp health and calcific healing of a complicated crown–root fracture with additional root fracture in a maxillary incisor: A case report

BACKGROUND Complicated crown–root fracture (CRF) involves severe injury to the crown, root,and pulp, and may be accompanied by multiple root fractures. The loss of a toothhas lifelong consequences for children and teenagers, but the maintenance of pulphealth and the calcific healing of multiple root fractures are rarely reported in theliterature.CASE SUMMARY This case reports healing of a permanent tooth with complicated crown–root andadditional root fractures, in which pulp health was maintained. A 10-year-old girlfell and fractured the root of her maxillary left central incisor at the cervical level.After the coronal fragment was repositioned, the tooth was splinted until thetooth was no longer mobile, 2 years later. Eight years after treatment, the toothhas remained asymptomatic with vital pulp and localized gingival overgrowth.Cone-beam computed tomography revealed not only calcified healing of the CRFbut also spontaneous healing in an additional undiagnosed root fracture. Thefracture line on the enamel could not be healed by hard tissue and formed agroove in the cervical crown. It was speculated that the groove was related to thelocalized gingival overgrowth.CONCLUSION This case provides a clinical perspective of the treatment of a tooth with acomplicated CRF and an additional root fracture.

Advancements and challenges in neuroimaging for the diagnosis of intracranial aneurysms:Addressing false positive diagnoses and emerging techniques

Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.

Role of photon-counting computed tomography in pediatric cardiovascular imaging

Photon-counting computed tomography(PCCT)represents a significant advancement in pediatric cardiovascular imaging.Traditional CT systems employ energy-integrating detectors that convert X-ray photons into visible light,whereas PCCT utilizes photon-counting detectors that directly transform X-ray photons into electric signals.This direct conversion allows photon-counting detectors to sort photons into discrete energy levels,thereby enhancing image quality through superior noise reduction,improved spatial and contrast resolution,and reduced artifacts.In pediatric applications,PCCT offers substantial benefits,including lower radiation doses,which may help reduce the risk of malignancy in pediatric patients,with perhaps greater potential to benefit those with repeated exposure from a young age.Enhanced spatial resolution facilitates better visualization of small structures,vital for diagnosing congenital heart defects.Additionally,PCCT’s spectral capabilities improve tissue characterization and enable the creation of virtual monoenergetic images,which enhance soft-tissue contrast and potentially reduce contrast media doses.Initial clinical results indicate that PCCT provides superior image quality and diagnostic accuracy compared to conven-tional CT,particularly in challenging pediatric cardiovascular cases.As PCCT technology matures,further research and standardized protocols will be essential to fully integrate it into pediatric imaging practices,ensuring optimized diagnostic outcomes and patient safety.

Congenital anomalies of coronary artery misdiagnosed as coronary dilatations in Kawasaki disease:A clinical predicament

BACKGROUND 2D-echocardiography(2DE)has been the primary imaging modality in children with Kawasaki disease(KD)to assess coronary arteries.AIM To report the presence and implications of incidental congenital coronary artery anomalies that had been misinterpreted as coronary artery abnormalities(CAAs)on 2DE.METHODS Records of children diagnosed with KD,who underwent computed tomography coronary angiography(CTCA)at our center between 2013-2023 were reviewed.We identified 3 children with congenital coronary artery anomalies in this cohort on CTCA.Findings of CTCA and 2DE were compared in these 3 children.RESULTS Of the 241 patients with KD who underwent CTCA,3(1.24%)had congenital coronary artery anomalies on CTCA detected incidentally.In all 3 patients,baseline 2DE had identified CAAs.CTCA was then performed for detailed evaluation as per our unit protocol.One(11-year-boy)amongst the 3 patients had complete KD,while the other two(3.3-year-boy;4-month-girl)had incomplete KD.CTCA revealed separate origins of left anterior descending artery and left circumflex from left sinus[misinterpreted as dilated left main coronary artery(LCA)on 2DE],single coronary artery(interpreted as dilated LCA on 2DE)and dilated right coronary artery on 2DE in case of anomalous origin of LCA from the main pulmonary artery.The latter one was subsequently operated upon.CONCLUSION CTCA is essential for detailed assessment of coronary arteries in children with KD especially in cases where there is suspicion of congenital coronary artery anomalies.Relying solely on 2DE may not be sufficient in such cases,and findings from CTCA can significantly impact therapeutic decision-making.

On the Toggling-Branching Recurrence of Computability Logic

We introduce a new, substantially simplified version of the toggling-branching recurrence operation of com- putability logic, prove its equivalence to Japaridze＇s old, ＂canonical＂ version, and also prove that both versions preserve the static property of their arguments.

17例耳硬化症患者的临床与影像学分析

目的分析17例耳硬化症患者的临床特征、影像学表现及手术治疗效果。方法收集2020年5月~2023年5月在湖州市中心医院接受手术治疗的17例(17耳)耳硬化症患者临床、影像学资料,分析其临床表现、颞骨CT影像学表现及手术前后纯音测听结果变化。结果17例(17耳)患者中,11耳(64.71%)为前庭窗型,表现为进行性传导性听力损失,其中9耳有耳鸣,3耳有轻微平衡问题;混合型6耳(35.29%)显示混合性听力损失,5耳有耳鸣,3耳有偶发性平衡障碍。影像学上,前庭窗型显示镫骨底板区域骨质增厚、前庭窗密度增加;混合型则显示镫骨底板增厚及耳蜗周围密度减低,1耳可见“双环征”,两种类型耳硬化症患者骨密度差异无统计学意义(P>0.05)。术后均未见耳鸣加重或其他严重并发症,仅2例(11.76%)出现暂时性头晕,术后随访显示术区恢复良好,无感染或其他迟发性并发症;术后听力测试显示气导阈值、气骨导差较术前显著改善(P均<0.05)。结论前庭窗型和混合型耳硬化症的影像学和临床表现各有特点,镫骨成形术可显著改善听力,降低气导阈值和气骨导差,且手术安全、并发症少。

Understanding the Theory of Karp, Miller and Winograd

The objective of this tutorial is to present the fundamental theory of Karp, Miller and Winograd, whose seminal paper laid the foundations regarding the systematic description of the organization of computations in systems of uniform recurrent equations by means of graph structures, via the definition of computability conditions and techniques for the construction of one-dimensional and multi-dimensional scheduling functions. Besides the description of this theory, the paper presents improvements and revisions made by other authors and furthermore, points out the differences regarding the conditions of causality and dependency between the general case of systems of recurrent equations and the special case of multiple nested loops.

基于高空平台的边缘计算卸载:网络、算法和展望

高空平台(high altitude platform,HAP)技术与多接入边缘计算(multi-access edge computing,MEC)技术的结合将MEC服务器部署区域由地面扩展到空中,打破传统地面MEC网络的局限性,为用户提供无处不在的计算卸载服务。针对基于HAP的MEC卸载研究进行综述,首先,从HAP计算节点的优势、网络组成部分、网络结构、主要挑战及其应对技术4个方面分析基于HAP的MEC网络;其次,分别从图论、博弈论、机器学习、联邦学习等理论的角度对基于HAP的MEC卸载算法进行横向分析和纵向对比;最后,指出基于HAP的MEC卸载技术目前存在的问题,并对该技术的未来研究方向进行展望。

Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

Computing Power Network:A Survey

With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.

侧风下磁浮列车-箱梁组合系统气动特性

与轮轨列车-桥梁组合系统不同,常导磁浮列车-桥梁系统采用“车抱轨”的结构形式,且列车底部与桥梁之间的空气通道极其狭窄,使得侧风下磁浮列车-桥梁组合系统的空气流动、气动力出现新的特征。本文以常导抱轨式高速磁浮列车和简支箱梁桥为研究对象,建立侧风数值分析模型,探讨组合系统的雷诺数效应,确定合适的模拟风速。在此基础上,对侧风下磁浮列车-箱梁组合系统的侧风气动特性进行分析,为磁浮交通的抗风运营安全提供参考。结果表明:磁浮列车-箱梁组合系统的气动特性与雷诺数密切相关,列车、箱梁气动性能受组合影响变化较大,线间距对系统气动性能的影响不明显,增大梁高会使系统气动力略有增加。

Investigation of pore geometry influence on fluid flow in heterogeneous porous media:A pore-scale study

Brazilian pre-salt reservoirs are renowned for their intricate pore networks and vuggy nature,posing significant challenges in modeling and simulating fluid flow within these carbonate reservoirs.Despite possessing excellent petrophysical properties,such as high porosity and permeability,these reservoirs typically exhibit a notably low recovery factor,sometimes falling below 10%.Previous research has indicated that various enhanced oil recovery(EOR)methods,such as water alternating gas(WAG),can substantially augment the recovery factor in pre-salt reservoirs,resulting in improvements of up to 20%.Nevertheless,the fluid flow mechanism within Brazilian carbonate reservoirs,characterized by complex pore geometry,remains unclear.Our study examines the behavior of fluid flow in a similar heterogeneous porous material,utilizing a plug sample obtained from a vugular segment of a Brazilian stromatolite outcrop,known to share analogies with certain pre-salt reservoirs.We conducted single-phase and multi-phase core flooding experiments,complemented by medical-CT scanning,to generate flow streamlines and evaluate the efficiency of water flooding.Subsequently,micro-CT scanning of the core sample was performed,and two cross-sections from horizontal and vertical plates were constructed.These cross-sections were then employed as geometries in a numerical simulator,enabling us to investigate the impact of pore geometry on fluid flow.Analysis of the pore-scale modeling and experimental data unveiled that the presence of dead-end pores and vugs results in a significant portion of the fluid remaining stagnant within these regions.Consequently,the injected fluid exhibits channeling-like behavior,leading to rapid breakthrough and low areal swept efficiency.Additionally,the numerical simulation results demonstrated that,irrespective of the size of the dead-end regions,the pressure variation within the dead-end vugs and pores is negligible.Despite the stromatolite's favorable petrophysical properties,including relatively high porosity and permeability,as well as the presence of interconnected large vugs,the recovery factor during water flooding remained low due to early breakthrough.These findings align with field data obtained from pre-salt reservoirs,providing an explanation for the observed low recovery factor during water flooding in such reservoirs.

从信号到知识——基于人工智能的医学影像裸数据诊断价值初探

Encouraging and astonishing developments have recently been achieved in image-based diagnostic technology.Modern medical care and imaging technology are becoming increasingly inseparable.However,the current diagnosis pattern of signal to image to knowledge inevitably leads to information distortion and noise introduction in the procedure of image reconstruction(from signal to image).Artificial intelligence(AI)technologies that can mine knowledge from vast amounts of data offer opportunities to disrupt established workflows.In this prospective study,for the first time,we develop an AI-based signal-toknowledge diagnostic scheme for lung nodule classification directly from the computed tomography(CT)raw data(the signal).We find that the raw data achieves almost comparable performance with CT,indicating that it is possible to diagnose diseases without reconstructing images.Moreover,the incorporation of raw data through three common convolutional network structures greatly improves the performance of the CT models in all cohorts(with a gain ranging from 0.01 to 0.12),demonstrating that raw data contains diagnostic information that CT does not possess.Our results break new ground and demonstrate the potential for direct signal-to-knowledge domain analysis.