AIMC Topic: Cohort Studies
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Development and Evaluation of a Convolutional Neural Network for Microscopic Diagnosis Between Pleomorphic Adenoma and Carcinoma Ex-Pleomorphic Adenoma.
Head & neck
Oct 27, 2024
AIMS: To develop a model capable of distinguishing carcinoma ex-pleomorphic adenoma from pleomorphic adenoma using a convolutional neural network architecture.
Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.
PloS one
Oct 22, 2024
INTRODUCTION AND OBJECTIVES: Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk ...
Artificial intelligence-assisted oculo-gait measurements for cognitive impairment in cerebral small vessel disease.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Oct 16, 2024
INTRODUCTION: Oculomotor and gait dysfunctions are closely associated with cognition. However, oculo-gait patterns and their correlation with cognition in cerebral small vessel disease (CSVD) remain unclear.
A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients.
Academic radiology
Oct 15, 2024
RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the capability of an ultrasound (US)-based deep learning (DL) nomogram for predicting axillary lymph node (ALN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients and ...
Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study.
Journal of clinical anesthesia
Oct 14, 2024
BACKGROUND: Intensive care units (ICUs) harbor the sickest patients with the utmost needs of medical care. Discharge from ICU needs to consider the reason for admission and stability after ICU care. Organ dysfunction or instability after ICU discharg...
Gene-diet interactions in carbonated sugar-sweetened beverage consumption and metabolic syndrome risk: A machine learning analysis in a large hospital-based cohort.
Clinical nutrition ESPEN
Oct 11, 2024
BACKGROUND AND AIM: Carbonated sugar-sweetened beverages (CSSB) intake has been increasingly linked to metabolic diseases. To investigate the association between CSSB intake and metabolic syndrome (MetS) risk, and the interaction between genetic pred...
One-year employment outcome prediction after traumatic brain injury: A CENTER-TBI study.
Disability and health journal
Oct 10, 2024
BACKGROUND: Traumatic brain injury (TBI) can come with long term consequences for functional outcome that can complicate return to work.
Generation of a virtual cohort of TAVI patients for in silico trials: a statistical shape and machine learning analysis.
Medical & biological engineering & computing
Oct 10, 2024
PURPOSE: In silico trials using computational modeling and simulations can complement clinical trials to improve the time-to-market of complex cardiovascular devices in humans. This study aims to investigate the significance of synthetic data in deve...
A machine learning approach in a monocentric cohort for predicting primary refractory disease in Diffuse Large B-cell lymphoma patients.
PloS one
Oct 1, 2024
INTRODUCTION: Primary refractory disease affects 30-40% of patients diagnosed with DLBCL and is a significant challenge in disease management due to its poor prognosis. Predicting refractory status could greatly inform treatment strategies, enabling ...
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study.
The lancet. Healthy longevity
Sep 30, 2024
BACKGROUND: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge here...
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