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Chronic Kidney Disease (CKD), where delayed recognition implies premature mortality, is currently experiencing a globally increasing incidence and high cost to health systems. Data mining allows discovering subtle patterns in CKD indicators…

Studying physiology over a broad population for long periods of time is difficult primarily because collecting human physiologic data is intrusive, dangerous, and expensive. Electronic health record (EHR) data promise to support the…

Stroke is widely considered as the second most common cause of mortality. The adverse consequences of stroke have led to global interest and work for improving the management and diagnosis of stroke. Various techniques for data mining have…

Artificial intelligence and deep learning are increasingly applied in the clinical domain, particularly for early and accurate disease detection using medical imaging and sound. Due to limited trained personnel, there is a growing demand…

Heart failure (HF) is a leading cause of morbidity, mortality, and health care costs. Prolonged conduction through the myocardium can occur with HF, and a device-driven approach, termed cardiac resynchronization therapy (CRT), can improve…

Background:Adverse reproductive history is a multisystemic risk factor, but evidence is constrained by isolated outcome studies, limited adjustment, and non-interpretable algorithmic models. We re-frame the estimand from prediction to…

Background: Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However, assessment by pathologists is hindered by challenges such as substantial time requirements,…

Background: Colorectal adenocarcinoma (CRC) remains a leading cause of cancer-related mortality worldwide, with variable patient outcomes despite treatment advances. Traditional prognostic methods based on clinicopathological variables…

Chronic Kidney Disease (CKD) has infected almost 800 million people around the world. Around 1.7 million people die each year because of it. Detecting CKD in the initial stage is essential for saving millions of lives. Many researchers have…

Assessing the severity of rheumatoid arthritis (RA) using the Total Sharp/Van Der Heijde Score (TSS) is crucial, but manual scoring is often time-consuming and subjective. This study introduces an Automated Radiographic Sharp Scoring…

We explore the emergence of persistent infection in a closed region where the disease progression of the individuals is given by the SIRS model, with an individual becoming infected on contact with another infected individual within a given…

Visual summarization of clinical data collected on patients contained within the electronic health record (EHR) may enable precise and rapid triage at the time of patient presentation to an emergency department (ED). The triage process is…

Objective: To improve prediction of Chronic Kidney Disease (CKD) progression to End Stage Renal Disease (ESRD) using machine learning (ML) and deep learning (DL) models applied to an integrated clinical and claims dataset of varying…

Electronic Health Records (EHR) are generated from clinical routine care recording valuable information of broad patient populations, which provide plentiful opportunities for improving patient management and intervention strategies in…

The utilization of Electronic Health Records (EHRs) for clinical risk prediction is on the rise. However, strict privacy regulations limit access to comprehensive health records, making it challenging to apply standard machine learning…

Chronic diseases such as diabetes are quite prevalent in the world and are responsible for a significant number of deaths per year. In addition, treatments for such chronic diseases account for a high healthcare cost. However, research has…

The healthcare sector has experienced a rapid accumulation of digital data recently, especially in the form of electronic health records (EHRs). EHRs constitute a precious resource that IS researchers could utilize for clinical applications…

Rheumatoid Arthritis (RA) is a chronic, autoimmune disease which primarily affects the joint's synovial tissue. It is a highly heterogeneous disease, with wide cellular and molecular variability observed in synovial tissues. Over the last…

Accurate prediction of future risk and disease progression in sepsis is clinically important for early warning and timely intervention in intensive care. However, short-window sepsis prediction remains challenging, because shorter…

Linear Discriminant Analysis (LDA) is a well-known technique for feature extraction and dimension reduction. The performance of classical LDA, however, significantly degrades on the High Dimension Low Sample Size (HDLSS) data for the…