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Dementia Overdiagnosis in Younger, Higher Educated Individuals Based on MMSE Alone: Analysis Using Deep Learning Technology.
Journal of Korean medical science
Mar 10, 2025
BACKGROUND: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment,...
A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 10, 2025
BACKGROUND: To construct and assess a deep learning (DL) signature that employs computed tomography imaging to predict the expression status of programmed cell death ligand 1 in patients with bladder cancer (BCa).
Development of a deep learning-based model for guiding a dissection during robotic breast surgery.
Breast cancer research : BCR
Mar 10, 2025
BACKGROUND: Traditional surgical education is based on observation and assistance in surgical practice. Recently introduced deep learning (DL) techniques enable the recognition of the surgical view and automatic identification of surgical landmarks. ...
Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease.
Genome biology
Mar 10, 2025
BACKGROUND: Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been limited by phenotyping challenges and ...
Automated deep learning-based assessment of tumour-infiltrating lymphocyte density determines prognosis in colorectal cancer.
Journal of translational medicine
Mar 10, 2025
BACKGROUND: The presence of tumour-infiltrating lymphocytes (TILs) is a well-established prognostic biomarker across multiple cancer types, with higher TIL counts being associated with lower recurrence rates and improved patient survival. We aimed to...
Generative AI-Enabled Therapy Support Tool for Improved Clinical Outcomes and Patient Engagement in Group Therapy: Real-World Observational Study.
Journal of medical Internet research
Mar 10, 2025
BACKGROUND: Cognitive behavioral therapy (CBT) is a highly effective treatment for depression and anxiety disorders. Nonetheless, a substantial proportion of patients do not respond to treatment. The lack of engagement with therapeutic materials and ...
Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms.
Physiological measurement
Mar 10, 2025
. Risk stratification of hypertension plays a crucial role in the treatment decisions and medication guidance during clinical practices. Although fruitful achievements have been reported on risk stratification of hypertension, the potential use of am...
Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU.
International journal of medical informatics
Mar 9, 2025
BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for ischemic stroke patients in the intensive care unit (ICU). However, the interpretation and translation of predictive models into clinical applications ar...
Artificial intelligence driven plaque characterization and functional assessment from CCTA using OCT-based automation: A prospective study.
International journal of cardiology
Mar 9, 2025
BACKGROUND: We aimed to develop and validate an Artificial Intelligence (AI) model that leverages CCTA and optical coherence tomography (OCT) images for automated analysis of plaque characteristics and coronary function.
Addressing underestimation and explanation of retinal fundus photo-based cardiovascular disease risk score: Algorithm development and validation.
Computers in biology and medicine
Mar 9, 2025
OBJECTIVE: To resolve the underestimation problem and investigate the mechanism of the AI model which employed to predict cardiovascular disease (CVD) risk scores from retinal fundus photos.
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