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Risk

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A machine learning based exploration of COVID-19 mortality risk.

PloS one
Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invas...

The use of a next-generation sequencing-derived machine-learning risk-prediction model (OncoCast-MPM) for malignant pleural mesothelioma: a retrospective study.

The Lancet. Digital health
BACKGROUND: Current risk stratification for patients with malignant pleural mesothelioma based on disease stage and histology is inadequate. For some individuals with early-stage epithelioid tumours, a good prognosis by current guidelines can progres...

Ethics of AI in Pathology: Current Paradigms and Emerging Issues.

The American journal of pathology
Deep learning has rapidly advanced artificial intelligence (AI) and algorithmic decision-making (ADM) paradigms, affecting many traditional fields of medicine, including pathology, which is a heavily data-centric specialty of medicine. The structured...

The impact of recency and adequacy of historical information on sepsis predictions using machine learning.

Scientific reports
Sepsis is a major public and global health concern. Every hour of delay in detecting sepsis significantly increases the risk of death, highlighting the importance of accurately predicting sepsis in a timely manner. A growing body of literature has ex...

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.

BMJ (Clinical research ed.)
OBJECTIVE: To assess the methodological quality of studies on prediction models developed using machine learning techniques across all medical specialties.

Real-Time Stress Level Feedback from Raw Ecg Signals for Personalised, Context-Aware Applications Using Lightweight Convolutional Neural Network Architectures.

Sensors (Basel, Switzerland)
Human stress is intricately linked with mental processes such as decision making. Public protection practitioners, including Law Enforcement Agents (LEAs), are forced to make difficult decisions during high-pressure operations, under strenuous circum...

Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth.

Scientific reports
Postpartum hemorrhage is the leading cause of maternal morbidity. Clinical prediction of postpartum hemorrhage remains challenging, particularly in the case of a vaginal birth. We studied machine learning models to predict postpartum hemorrhage. Wome...

A weighted patient network-based framework for predicting chronic diseases using graph neural networks.

Scientific reports
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We...

Single-Examination Risk Prediction of Severe Retinopathy of Prematurity.

Pediatrics
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...