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MALDI-TOF mass spectrometry combined with machine learning algorithms to identify protein profiles related to malaria infection in human sera from Côte d'Ivoire.
Malaria journal
Apr 18, 2025
BACKGROUND: In sub-Saharan Africa, Plasmodium falciparum is the most prevalent species of malaria parasites. In endemic areas, malaria is mainly diagnosed using microscopy or rapid diagnostic tests (RDTs), which have limited sensitivity, and microsco...
A machine learning-based severity stratification tool for high altitude pulmonary edema.
BMC medical informatics and decision making
Apr 18, 2025
This study aimed to identify key predictors for the severity of High Altitude Pulmonary Edema (HAPE) to assist clinicians in promptly recognizing severely affected patients in the emergency department, thereby reducing associated mortality rates. Mul...
A machine learning approach to investigate the role of fear of pain, personal experience, and vicarious learning in dental anxiety.
BMC oral health
Apr 18, 2025
BACKGROUND: Dental anxiety is a pervasive problem worldwide, leading to avoidance of dental care, resulting in oral health problems and impacting daily life through social withdrawal and work absenteeism. Addressing this fear is an important public h...
Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology.
BMC gastroenterology
Apr 18, 2025
BACKGROUND AND AIM: Colorectal cancer is among the most prevalent and deadliest cancers. Early prediction of metastasis in patients with colorectal cancer is crucial in preventing it from the advanced stages and enhancing the prognosis among these pa...
Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.
Scientific reports
Apr 18, 2025
The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, and clinician diagnoses by heavily weighting lifestyle factors in the predictions. Machine learning m...
Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome.
World journal of urology
Apr 18, 2025
PURPOSE: To identify biomarkers for diagnosis and classification of interstitial cystitis/bladder pain syndrome (IC/BPS) by urinary lipidomics coupled with machine learning.
Effect of Uncertainty-Aware AI Models on Pharmacists' Reaction Time and Decision-Making in a Web-Based Mock Medication Verification Task: Randomized Controlled Trial.
JMIR medical informatics
Apr 18, 2025
BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems are increasingly used in health care. Uncertainty-aware AI presents the model's confidence in its decision alongside its prediction, whereas black-box AI only provides a...
Stigmatisation of gambling disorder in social media: a tailored deep learning approach for YouTube comments.
Harm reduction journal
Apr 18, 2025
BACKGROUND: The stigmatisation of gamblers, particularly those with a gambling disorder, and self-stigmatisation are considered substantial barriers to seeking help and treatment. To develop effective strategies to reduce the stigma associated with g...
Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation.
JMIR medical informatics
Apr 18, 2025
BACKGROUND: Delirium is common in hospitalized patients and is correlated with increased morbidity and mortality. Despite this, delirium is underdiagnosed, and many institutions do not have sufficient resources to consistently apply effective screeni...
Multi-modal multi-task deep neural networks for sleep disordered breathing assessment using cardiac and audio signals.
International journal of medical informatics
Apr 17, 2025
BACKGROUND AND OBJECTIVE: Sleep disordered breathing (SDB) is one of the most common sleep disorders and has short-term consequences for daytime functioning while being a risk factor for several conditions, such as cardiovascular disease. Polysomnogr...
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