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Factors inducing cutaneous adverse reactions in cancer patients treated with PD-1 and PD-L1 inhibitors: a machine-learning algorithm approach.

Immunopharmacology and immunotoxicology
BACKGROUND: Immune checkpoint inhibitors (ICIs) show promise in cancer treatment but can lead to immune-related adverse events (irAEs), notably affecting the skin. Understanding the factors behind these skin reactions is crucial for effective managem...

How do older adults react to social robots' offspring-like voices.

Social science & medicine (1982)
Social robots are being developed as a technological solution to alleviate older adults' loneliness due to separation from their offspring. This study explores how and why offspring-like voices affect older adults' acceptance of social robots from an...

Implementing deep learning on edge devices for snoring detection and reduction.

Computers in biology and medicine
This study introduces MinSnore, a novel deep learning model tailored for real-time snoring detection and reduction, specifically designed for deployment on low-configuration edge devices. By integrating MobileViTV3 blocks into the Dynamic MobileNetV3...

A novel classical machine learning framework for early sepsis prediction using electronic health record data from ICU patients.

Computers in biology and medicine
Sepsis, a life-threatening condition triggered by the body's response to infection, remains a significant global health challenge, annually affecting millions in the United States alone with substantial mortality and healthcare costs. Early predictio...

Comprehensive prediction of outcomes in patients with ST elevation myocardial infarction (STEMI) using tree-based machine learning algorithms.

Computers in biology and medicine
ST elevation myocardial infarction (STEMI), a subtype of acute coronary syndrome, is one of the leading causes of morbidity and mortality. Revascularization using primary percutaneous coronary intervention (PPCI) is the gold standard treatment. Despi...

Noninvasive Total Cholesterol Level Measurement Using an E-Nose System and Machine Learning on Exhaled Breath Samples.

ACS sensors
In this paper, the first e-nose system coupled with machine learning algorithm for noninvasive measurement of total cholesterol level based on exhaled air sample was proposed. The study was conducted with the participation of 151 people, from whom a ...

Screening for severe coronary stenosis in patients with apparently normal electrocardiograms based on deep learning.

BMC medical informatics and decision making
BACKGROUND: Patients with severe coronary arterystenosis may present with apparently normal electrocardiograms (ECGs), making it difficult to detect adverse health conditions during routine screenings or physical examinations. Consequently, these pat...

Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding.

Journal of translational medicine
BACKGROUND: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) infection is a challenge in the...

Establishing a machine learning dementia progression prediction model with multiple integrated data.

BMC medical research methodology
OBJECTIVE: Dementia is a significant medical and social issue in most developed countries. Practical tools for predicting the progression of degenerative dementia are highly valuable. Machine learning (ML) methods facilitate the construction of effec...

A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses.

Scientific reports
Decreasing speed and stride length over successive races have been shown to be associated with musculoskeletal injury (MSI) in racehorses, demonstrating the potential for early detection of MSI through longitudinal monitoring of changes in stride cha...