AI Medical Compendium Topic

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Adolescent

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Exploring machine learning algorithms to predict not using modern family planning methods among reproductive age women in East Africa.

BMC health services research
BACKGROUND: The use of the modern family planning method provides chances for women to reach optimal child spacing, increase quality of life, increase economic status, achieve the desired family size, and prevent unsafe abortions and maternal and per...

Leveraging machine learning models for anemia severity detection among pregnant women following ANC: Ethiopian context.

BMC public health
BACKGROUND: Anemia during pregnancy is a significant public health concern, particularly in resource-limited settings. Machine learning (ML) offers promising avenues for improved anemia detection and management. This study investigates the potential ...

Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.

BMC infectious diseases
BACKGROUND: During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred frequently, yet the risk factors and predictive models for TR remain unclear. This study aims to identi...

Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury.

BMC psychiatry
BACKGROUND: Nonsuicidal self-injury is a common health problem in adolescents and associated with future suicidal behavior. Predicting who will benefit from treatment is an urgent and a critical first step towards personalized treatment approaches. M...

Profiling the AI speaker user: Machine learning insights into consumer adoption patterns.

PloS one
The objective of this study is to identify the characteristics of users of AI speakers and predict potential consumers, with the aim of supporting effective advertising and marketing strategies in the fast-evolving media technology landscape. To do s...

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder.

Journal of affective disorders
BACKGROUND: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder...

Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: This study aims to develop an interpretable machine learning (ML) predictive model to assess its efficacy in predicting postoperative recurrence in pediatric chronic rhinosinusitis (CRS).

Machine Learning-Based Prediction Model for ICU Mortality After Continuous Renal Replacement Therapy Initiation in Children.

Critical care explorations
BACKGROUND: Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and ...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

Journal of sports sciences
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...

Brain networks and intelligence: A graph neural network based approach to resting state fMRI data.

Medical image analysis
Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying...