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Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia.
Frontiers in immunology
Feb 24, 2025
BACKGROUND: Neutrophil extracellular traps (NETs) play pivotal roles in various pathological processes. The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.
Development and validation of predictive models for diabetic retinopathy using machine learning.
PloS one
Feb 24, 2025
OBJECTIVE: This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks.
Novel Robotic Balloon-Based Device for Wrist-Extension Therapy of Hemiparesis Stroke Patients.
Sensors (Basel, Switzerland)
Feb 23, 2025
Upper-limb paresis is one of the main complications after stroke. It is commonly associated with impaired wrist-extension function. Upper-limb paresis can place a tremendous burden on stroke survivors and their families. A novel soft-actuator device,...
Regional Cerebral Atrophy Contributes to Personalized Survival Prediction in Amyotrophic Lateral Sclerosis: A Multicentre, Machine Learning, Deformation-Based Morphometry Study.
Annals of neurology
Feb 22, 2025
OBJECTIVE: Accurate personalized survival prediction in amyotrophic lateral sclerosis is essential for effective patient care planning. This study investigates whether grey and white matter changes measured by magnetic resonance imaging can improve i...
Epilepsy surgery candidate identification with artificial intelligence: An implementation study.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Feb 22, 2025
BACKGROUND: To (a) evaluate the effect of a machine learning algorithm in the identification of patients suitable for epilepsy surgery evaluation, and (b) examine the performance of a large language model (LLM) in the collation of key pieces of infor...
Multimodal Artificial Intelligence-Based Virtual Biopsy for Diagnosing Abdominal Lavage Cytology-Positive Gastric Cancer.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 22, 2025
Gastric cancer with peritoneal dissemination remains a significant clinical challenge due to its poor prognosis and difficulty in early detection. This study introduces a multimodal artificial intelligence-based risk stratification assessment (RSA) m...
Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model.
Ecotoxicology and environmental safety
Feb 22, 2025
Exposure to three primary xenoestrogens (XEs), including phthalates, parabens, and phenols, has been strongly associated with chronic kidney disease (CKD). An interpretable machine learning (ML) model was developed to predict CKD using data from the ...
Fast, smart, and adaptive: using machine learning to optimize mental health assessment and monitor change over time.
Scientific reports
Feb 22, 2025
In mental health, accurate symptom assessment and precise measurement of patient conditions are crucial for clinical decision-making and effective treatment planning. Traditional assessment methods can be burdensome, especially for vulnerable populat...
Machine learning-based prediction of post-induction hypotension: identifying risk factors and enhancing anesthesia management.
BMC medical informatics and decision making
Feb 22, 2025
BACKGROUND: Post-induction hypotension (PIH) increases surgical complications including myocardial injury, acute kidney injury, delirium, stroke, prolonged hospitalization, and endangerment of the patient's life. Machine learning is an effective tool...
Artificial intelligence assessment of tissue-dissection efficiency in laparoscopic colorectal surgery.
Langenbeck's archives of surgery
Feb 22, 2025
PURPOSE: Several surgical-skill assessment tools emphasize the importance of efficient tissue-dissection, whose assessment relies on human judgment and is thus subject to bias. Automated assessment may help solve this problem. This study aimed to ver...
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