AIMC Topic: Humans

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The Cost-Effectiveness of an Artificial Intelligence-Based Population-Wide Screening Program for Primary Open-Angle Glaucoma in The Netherlands.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Population-wide screening for primary open-angle glaucoma (glaucoma) is typically not cost-effective because of low prevalence and high costs. We evaluated the cost-effectiveness of repeated artificial intelligence (AI)-based glaucoma scr...

Using Machine Learning to Match Clients and Therapy Providers: Evaluating Clinical Quality and Cost of Care.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Matching clients in need of mental healthcare with providers who will deliver high quality treatment presents a substantial challenge. Machine learning models hold potential for predicting the best pairings from a multitude of data points...

A Innovative Strategy for Identifying Subtypes Through the Analysis of Multi-Omics Data with Adversarial Autoencoders.

Journal of computational biology : a journal of computational molecular cell biology
Cancer is a disease that is both complex and diverse, and effective diagnosis and treatment require an accurate depiction of tumor subtypes. Traditional methods of cancer identification, which rely on clinical and histopathological criteria, have lim...

Screening of Glaucoma in High-Risk Minority Populations.

Journal of glaucoma
PRECIS: This chapter reviews the current recommendations on screening for open angle glaucoma in Black and Hispanic populations. Strategies for increasing case-finding and decreasing cost, with emphasis on evolving technologies, are presented.

Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments.

BMJ health & care informatics
OBJECTIVE: Machine learning (ML) models have emerged as tools to predict length of stay (LOS) and disposition decision (DD) in emergency departments (EDs) to combat overcrowding. However, site-specific ML models are not transferable to different site...

Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.

Pediatric surgery international
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...

Attention-based hybrid deep learning model with CSFOA optimization and G-TverskyUNet3+ for Arabic sign language recognition.

Scientific reports
Arabic sign language (ArSL) is a visual-manual language which facilitates communication among Deaf people in the Arabic-speaking nations. Recognizing the ArSL is crucial due to variety of reasons, including its impact on the Deaf populace, education,...

Prognostic predictions in psychosis: exploring the complementary role of machine learning models.

BMJ mental health
BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine learning (ML) shows promise in outcome prediction, it has not yet been integrated into clinical practi...

Unraveling the role of perineural invasion in cancer progression across multiple tumor types.

Medical oncology (Northwood, London, England)
Perineural invasion (PNI) refers to the infiltration of tumor cells into the connective tissue of nerves and is increasingly recognized as a pathological hallmark of multiple cancers, including pancreatic, prostate, colorectal, breast, and head and n...

Exploring semantic grounding in the posterior parietal cortex.

Brain structure & function
This study examines the evolving perspective on semantic processing, which has shifted from the traditional view of an isolated semantic memory system to one that recognizes the involvement of dynamic, distributed neural networks. Recent evidence sup...