AIMC Topic: Risk Assessment

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Application of artificial intelligence and machine learning for risk stratification acute kidney injury among hematopoietic stem cell transplantation patients: PCRRT ICONIC AI Initiative Group Meeting Proceedings.

Clinical nephrology
Acute kidney injury (AKI) is a frequent, severe complication of hematopoietic stem cell transplantation (HSCT) and is associated with an increased risk of morbidity and mortality. Recent advances in artificial intelligence (AI) and machine learning (...

[Legal Risk Assessment and Prevention in Artificial Intelligence-Assisted Health Care].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
With the wide application of new technologies such as large language models and generative artificial intelligence (AI) in the health care sector, artificial intelligence-assisted health care is confronted with new forms of legal risks. The algorithm...

A fusion model of manually extracted visual features and deep learning features for rebleeding risk stratification in peptic ulcers.

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVES: We propose a multi-feature fusion model based on manually extracted features and deep learning features from endoscopic images for grading rebleeding risk of peptic ulcers.

Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomas.

Neuro-oncology
BACKGROUND: Postoperative recurrence risk for pediatric low-grade gliomas (pLGGs) is challenging to predict by conventional clinical, radiographic, and genomic factors. We investigated if deep learning (DL) of magnetic resonance imaging (MRI) tumor f...

Application of machine learning for detecting high fall risk in middle-aged workers using video-based analysis of the first 3 steps.

Journal of occupational health
OBJECTIVES: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fa...

A novel machine learning-based cancer-specific cardiovascular disease risk score among patients with breast, colorectal, or lung cancer.

JNCI cancer spectrum
BACKGROUND: Cancer patients have up to a 3-fold higher risk for cardiovascular disease (CVD) than the general population. Traditional CVD risk scores may be less accurate for them. We aimed to develop cancer-specific CVD risk scores and compare them ...

Development and validation of an interpretable longitudinal preeclampsia risk prediction using machine learning.

PloS one
Preeclampsia is a pregnancy-specific disease characterized by new onset hypertension after 20 weeks of gestation that affects 2-8% of all pregnancies and contributes to up to 26% of maternal deaths. Despite extensive clinical research, current predic...

Sarcopenia prediction model based on machine learning and SHAP values for community-based older adults with cardiovascular disease in China.

Frontiers in public health
BACKGROUND: Sarcopenia (SP), is recognized as a complication of cardiovascular disease (CVD), but few relevant diagnostic models have been developed. This study aims to establish an interpretable diagnostic model for the occurrence of SP in older adu...

Preoperative kidney tumor risk estimation with AI: From logistic regression to transformer.

PloS one
We consider the problem of renal mass risk classification to support doctors in adjuvant treatment decisions following nephrectomy. Recommendation of adjuvant therapy based on the mass appearance poses two major challenges: first, morphologic pattern...