AIMC Topic: Aged

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Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics.

Journal of translational medicine
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health concern that necessitates early screening and timely intervention to improve prognosis. The current diagnostic protocols for MASLD involve complex procedu...

Developing a high-performance AI model for spontaneous intracerebral hemorrhage mortality prediction using machine learning in ICU settings.

BMC medical informatics and decision making
BACKGROUND: Spontaneous intracerebral hemorrhage (SICH) is a devastating condition that significantly contributes to high mortality rates. This study aims to construct a mortality prediction model for patients with SICH using four various artificial ...

Development and evaluation of a machine learning model for osteoporosis risk prediction in Korean women.

BMC women's health
BACKGROUND: The aim of this study was to develop a machine learning (ML) model for classifying osteoporosis in Korean women based on a large-scale population cohort study. This study also aimed to assess ML model performance compared with traditional...

A deep learning model for classification of chondroid tumors on CT images.

BMC cancer
BACKGROUND: Differentiating chondroid tumors is crucial for proper patient management. This study aimed to develop a deep learning model (DLM) for classifying enchondromas, atypical cartilaginous tumors (ACT), and high-grade chondrosarcomas using CT ...

Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning.

BMC cancer
BACKGROUND: Distinguishing between benign and malignant testicular lesions on clinical magnetic resonance imaging (MRI) is crucial for guiding treatment planning. However, conventional MRI-based radiomics to identify testicular cancer requires expert...

Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries.

Scientific reports
The most prevalent malignancy among women is breast cancer; hence, treatment approaches are needed in consideration of tumor characteristics and disease stage but also patient preference. Two surgical options, Mastectomy and Breast Conserving Surgery...

Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.

Scientific reports
This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney injury (AKI) in diabetic patients with heart failure (HF) during hospitalization. Using data from 1,457 patients in the MIMIC-IV database, the study ide...

A deep learning approach to remotely assessing essential tremor with handwritten images.

Scientific reports
Essential tremor (ET) is the most prevalent movement disorder, with its incidence increasing with age, significantly impacting motor functions and quality of life. Traditional methods for assessing ET severity are often time-consuming, subjective, an...

Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach.

JMIR medical informatics
BACKGROUND: Chronic pain is a complex condition that affects more than a quarter of people worldwide. The development and progression of chronic pain are unique to each individual due to the contribution of interacting biological, psychological, and ...