AIMC Topic: Aged

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Automated deep learning-based assessment of tumour-infiltrating lymphocyte density determines prognosis in colorectal cancer.

Journal of translational medicine
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...

Intelligent risk stratification of hypertension based on ambulatory blood pressure monitoring and machine learning algorithms.

Physiological measurement
. 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...

Factors associated with the development of severe asthma: A nationwide study (FINASTHMA).

Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology
BACKGROUND: Severe asthma presents a major challenge to health care and negatively affects the quality of life of patients. Understanding the factors predicting the development of severe asthma is limited.

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
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
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
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.

Dynamic HRV Monitoring and Machine Learning Predict NYHA Improvements in Acute Heart Failure Patients.

Computers in biology and medicine
Heart failure (HF) is marked by significant morbidity, mortality, and readmission rates, highlighting a critical need for accurate assessment of treatment efficacy. The New York Heart Association (NYHA) classification, while standard, falls short in ...

Development and validation of radiomics and deep transfer learning models to assess cognitive impairment in patients with cerebral small vessel disease.

Neuroscience
Cognitive impairment in cerebral small vessel disease (CSVD) progresses subtly but carries significant clinical consequences, necessitating effective diagnostic tools. This study developed and validated predictive models for CSVD-related cognitive im...

Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.

Endocrine
BACKGROUND: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RADS) category 3-5 are typically regarded as having varying degrees of malignancy risk, with the risk increasing from TI-RADS 3 to TI-RADS 5. While some ...