AIMC Topic: Machine Learning

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Role of fatty acid metabolism-related genes in periodontitis based on machine learning and bioinformatics analysis.

Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology
OBJECTIVES: This study aims to investigate the role of genes related to fatty acid metabolism in periodontitis through machine learning and bioinformatics methods.

Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study.

Health expectations : an international journal of public participation in health care and health policy
INTRODUCTION: Globally, many people experience mental health difficulties, and the current workforce capacity is insufficient to meet this demand, with growth not keeping pace with need. Digital devices that passively collect data and utilise machine...

Prediction of Post Traumatic Epilepsy Using MR-Based Imaging Markers.

Human brain mapping
Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Despite the high prevalence of PTE, current methods for predicting its occurrence remain limited. In this study, we aimed to ident...

Predicting Suicides Among US Army Soldiers After Leaving Active Service.

JAMA psychiatry
IMPORTANCE: The suicide rate of military servicemembers increases sharply after returning to civilian life. Identifying high-risk servicemembers before they leave service could help target preventive interventions.

Fair prediction of 2-year stroke risk in patients with atrial fibrillation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.

Leveraging artificial intelligence for advancements in reproductive health.

African journal of reproductive health
We are writing to address the growing interest in the role of artificial intelligence (AI) within healthcare, particularly in the field of reproductive health. As technology continues to evolve, AI offers an unprecedented opportunity to transform how...

[Application of CT Radiomics in Predicting Differentiation Level of Lung Adenocarcinoma].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: To investigate the value of prediction of the differentiation level in lung adenocarcinoma based on CT radiomics model.

Survival causal rule ensemble method considering the main effect for estimating heterogeneous treatment effects.

Statistics in medicine
With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship between treatment effects and patient characteristics. The treatment effects for patients with differ...

Machine Learning Reveals Aneuploidy Characteristics in Cancers: The Impact of BEX4.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Aneuploidy is crucial yet under-explored in cancer pathogenesis. Specifically, the involvement of brain expressed X-linked gene 4 () in microtubule formation has been identified as a potential aneuploidy mechanism. Nevertheless, 's compre...

Identification of KCNQ1 as a diagnostic biomarker related to endoplasmic reticulum stress for intervertebral disc degeneration based on machine learning and experimental evidence.

Medicine
Intervertebral disc degeneration (IDD) is a primary cause of low back pain and disability. Cellular senescence and apoptosis due to endoplasmic reticulum stress (ERS) are key in IDD pathology. Identifying biomarkers linked to ERS in IDD is crucial fo...