AIMC Topic: Aged

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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

Open heart
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ...

Developing a decision support tool to predict delayed discharge from hospitals using machine learning.

BMC health services research
BACKGROUND: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital...

A prediction study on the occurrence risk of heart disease in older hypertensive patients based on machine learning.

BMC geriatrics
OBJECTIVE: Constructing a predictive model for the occurrence of heart disease in elderly hypertensive individuals, aiming to provide early risk identification.

Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models.

Scientific reports
Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning ...

A benchmark of deep learning approaches to predict lung cancer risk using national lung screening trial cohort.

Scientific reports
Deep learning (DL) methods have demonstrated remarkable effectiveness in assisting with lung cancer risk prediction tasks using computed tomography (CT) scans. However, the lack of comprehensive comparison and validation of state-of-the-art (SOTA) mo...

A Radiomic-Clinical Model of Contrast-Enhanced Mammography for Breast Cancer Biopsy Outcome Prediction.

Academic radiology
RATIONALE AND OBJECTIVES: In the USA over 1 million breast biopsies are performed annually. Approximately 9.6% diagnostic exams were given Breast Imaging Reporting and Data System (BI-RADS) ≥4A, most of which are 4A/4B. Contrast-enhanced mammography ...

Prediction of p-phenylenediamine antioxidant concentrations in human urine using machine learning models.

Journal of hazardous materials
p-phenylenediamine antioxidants (PPDs) are extensively used in rubber manufacturing for their potent antioxidative properties, but PPDs and 2-anilino-5-[(4-methylpentan-2yl)amino]cyclohexa-2,5-diene-1,4-dione (6PPDQ) pose potential environmental and ...

Multimodal deep-learning model using pre-treatment endoscopic images and clinical information to predict efficacy of neoadjuvant chemotherapy in esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society
BACKGROUND: Neoadjuvant chemotherapy is standard for advanced esophageal squamous cell carcinoma, though often ineffective. Therefore, predicting the response to chemotherapy before treatment is desirable. However, there is currently no established m...

Utilizing artificial intelligence and cellular population data for timely identification of bacteremia in hospitalized patients.

International journal of medical informatics
BACKGROUND: Bacteremia is a critical condition with high mortality that requires prompt detection to prevent progression to life-threatening sepsis. Traditional diagnostic approaches, such as blood cultures, are time-consuming. This limitation has en...