AIMC Topic: Aged
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Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography.
JCO clinical cancer informatics
Feb 20, 2025
PURPOSE: Primary barriers to application of immune checkpoint inhibitor (ICI) therapy for cancer include severe side effects (such as potentially life threatening pneumonitis [PN]), which can cause the discontinuation of treatment. Predicting which p...
Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population: A machine learning approach.
PloS one
Feb 20, 2025
Inter-individual cognitive variability, influenced by genetic and environmental factors, is crucial for understanding typical cognition and identifying early cognitive disorders. This study investigated the association between serum protein expressio...
Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [F]PSMA-1007 PET/CT and multiparametric MRI.
European journal of nuclear medicine and molecular imaging
Feb 19, 2025
PURPOSE: Accurate prediction of adverse pathology (AP) in prostate cancer (PCa) patients is crucial for formulating effective treatment strategies. This study aims to develop and evaluate a multimodal deep learning model based on [F]PSMA-1007 PET/CT ...
CT-Based Machine Learning Radiomics Analysis to Diagnose Dysthyroid Optic Neuropathy.
Seminars in ophthalmology
Feb 19, 2025
PURPOSE: To develop CT-based machine learning radiomics models used for the diagnosis of dysthyroid optic neuropathy (DON).
Identification of a gene signature and prediction of overall survival of patients with stage IV colorectal cancer using a novel machine learning approach.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Feb 19, 2025
OBJECTIVE: We sought to characterize unique gene signature patterns associated with worse overall survival (OS) among patients with stage IV colorectal cancer (CRC) using a machine learning (ML) approach.
Electrocardiographic-Driven artificial intelligence Model: A new approach to predicting One-Year mortality in heart failure with reduced ejection fraction patients.
International journal of medical informatics
Feb 19, 2025
BACKGROUND: Despite the proliferation of heart failure (HF) mortality prediction models, their practical utility is limited. Addressing this, we utilized a significant dataset to develop and validate a deep learning artificial intelligence (AI) model...
Detection of Ocular Surface Squamous Neoplasia Using Artificial Intelligence With Anterior Segment Optical Coherence Tomography.
American journal of ophthalmology
Feb 19, 2025
PURPOSE: To develop and validate a deep learning (DL) model to differentiate ocular surface squamous neoplasia (OSSN) from pterygium and pinguecula using high-resolution anterior segment optical coherence tomography (AS-OCT).
Carcinoma, Squamous Cell
Pterygium
Diagnosis, Differential
Reproducibility of Results
Tomography, Optical Coherence
Humans
Anterior Eye Segment
Male
Artificial Intelligence
Conjunctival Neoplasms
Aged
Corneal Diseases
Middle Aged
Retrospective Studies
Adult
Aged, 80 and over
Deep Learning
Female
Sensitivity and Specificity
Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.
Computers in biology and medicine
Feb 19, 2025
BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal ...
Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients.
Journal of the American Heart Association
Feb 19, 2025
BACKGROUND: Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac intensive care units. An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been...
Automated identification of incidental hepatic steatosis on Emergency Department imaging using large language models.
Hepatology communications
Feb 19, 2025
BACKGROUND: Hepatic steatosis is a precursor to more severe liver disease, increasing morbidity and mortality risks. In the Emergency Department, routine abdominal imaging often reveals incidental hepatic steatosis that goes undiagnosed due to the ac...
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