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Mucoepidermoid carcinoma: Enhancing diagnostic accuracy and treatment strategy through machine learning models and web-based prognostic tool.
Journal of stomatology, oral and maxillofacial surgery
Dec 25, 2024
BACKGROUND: Oral cancer, particularly mucoepidermoid carcinoma (MEC), presents diagnostic challenges due to its histological diversity and rarity. This study aimed to develop machine learning (ML) models to predict survival outcomes for MEC patients ...
Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.
Aging cell
Dec 25, 2024
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...
Identifying potential medical aid beneficiaries using machine learning: A Korean Nationwide cohort study.
International journal of medical informatics
Dec 25, 2024
OBJECTIVE: To identify potential medical aid beneficiaries using demographic and medical history of individuals and analyzing important features qualitatively.
Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma.
CPT: pharmacometrics & systems pharmacology
Dec 25, 2024
We employed a mechanistic learning approach, integrating on-treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post-progression survival (PPS)-the duration from the time of document...
Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters.
Neurologia medico-chirurgica
Dec 25, 2024
This study aimed to investigate the patterns of anticoagulation therapy and coagulation parameters and to develop a prediction model to predict the type of anticoagulation therapy in geriatric patients with traumatic brain injury. A retrospective ana...
Effect of artificial intelligence-based video-game system on dysphagia in patients with stroke: A randomized controlled trial.
Clinical nutrition (Edinburgh, Scotland)
Dec 25, 2024
BACKGROUND AND AIMS: Post-stroke dysphagia is highly prevalent and causes complication. While video games have demonstrated potential to increase patient engagement in rehabilitation, their efficacy in stroke patients with dysphagia remains unclear. ...
Mortality Prediction in Patients With Breast Cancer by Artificial Neural Network Model and Elastic Net Regression.
Journal of research in health sciences
Dec 25, 2024
BACKGROUND: Breast cancer (BC) is the most common cancer in women, and it is important to identify models that can accurately predict mortality in patients with this cancer. The aim of the present study was to use the elastic net regression and artif...
12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.
Journal of electrocardiology
Dec 25, 2024
BACKGROUND AND PURPOSE: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electrical and structural changes, notably low voltage areas (LVAs) which are associated with poor ablation outcomes and increased thromboembolic risk. This ...
Development of a short form of the Geriatric Depression Scale-30 based on item response theory and the RiskSLIM algorithm.
General hospital psychiatry
Dec 25, 2024
Recently, methods of quickly and accurately screening for geriatric depression have attracted substantial attention. Short forms of the 30-item Geriatric Depression Scale have been developed based on classical test theory, such as the GDS-4, GDS-5, a...
Radiomics and deep learning models for glioblastoma treatment outcome prediction based on tumor invasion modeling.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Dec 25, 2024
PURPOSE: We investigate the feasibility of using a biophysically guided approach for delineating the Clinical Target Volume (CTV) in Glioblastoma Multiforme (GBM) by evaluating its impact on the treatment outcomes, specifically Overall Survival (OS) ...
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