AIMC Topic: Risk Factors

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Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data.

PLoS medicine
BACKGROUND: Suicide is a major public health concern globally. Accurately predicting suicidal behavior remains challenging. This study aimed to use machine learning approaches to examine the potential of the Swedish national registry data for predict...

Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level.

Journal of the American Heart Association
Background Stroke is a major cardiovascular disease that causes significant health and economic burden in the United States. Neighborhood community-based interventions have been shown to be both effective and cost-effective in preventing cardiovascul...

Predicting preventable hospital readmissions with causal machine learning.

Health services research
OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).

Personalized prediction of delayed graft function for recipients of deceased donor kidney transplants with machine learning.

Scientific reports
Machine learning (ML) has shown its potential to improve patient care over the last decade. In organ transplantation, delayed graft function (DGF) remains a major concern in deceased donor kidney transplantation (DDKT). To this end, we harnessed ML t...

The Use of Artificial Neural Network to Predict Surgical Outcomes After Inguinal Hernia Repair.

The Journal of surgical research
BACKGROUND: Inguinal hernia repair is one of the most commonly performed surgical procedures. We developed and validated an artificial neural network (ANN) model for the prediction of surgical outcomes and the analysis of risk factors for inguinal he...

Machine Learning Algorithms for the Prediction of Central Lymph Node Metastasis in Patients With Papillary Thyroid Cancer.

Frontiers in endocrinology
BACKGROUND: Central lymph node metastasis (CLNM) occurs frequently in patients with papillary thyroid cancer (PTC), but performing prophylactic central lymph node dissection is still controversial. There are no reliable models for predicting CLNM. Th...

Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study.

PloS one
BACKGROUND & AIMS: Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best ...

Development of a prognostic model for mortality in COVID-19 infection using machine learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Coronavirus disease 2019 (COVID-19) is a novel disease resulting from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has quickly risen since the beginning of 2020 to become a global pandemic. As a result of the rap...

Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. Even after a fracture occurs, high fracture risk remains widely underdiagnosed and undertreated. Comm...