AIMC Topic: Humans

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Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review.

International orthopaedics
PURPOSE: The purpose of this scoping review is to analyze the application of artificial intelligence (AI) in ultrasound (US) imaging for diagnosing carpal tunnel syndrome (CTS), with an aim to explore the potential of AI in enhancing diagnostic accur...

Machine Learning in Predicting Child Malnutrition: A Meta-Analysis of Demographic and Health Surveys Data.

International journal of environmental research and public health
BACKGROUND: Childhood malnutrition remains a significant global public health concern. The Demographic and Health Surveys (DHS) program provides specific data on child health across numerous countries. This meta-analysis aims to comprehensively asses...

GPT for RCTs? Using AI to determine adherence to clinical trial reporting guidelines.

BMJ open
OBJECTIVES: Adherence to established reporting guidelines can improve clinical trial reporting standards, but attempts to improve adherence have produced mixed results. This exploratory study aimed to determine how accurate a large language model gen...

Using artificial intelligence to improve healthcare delivery in select allied health disciplines: a scoping review protocol.

BMJ open
INTRODUCTION: Methods to adopt artificial intelligence (AI) in healthcare clinical practice remain unclear. The potential for rapid integration of AI-enabled technologies across healthcare settings coupled with the growing digital divide in the healt...

User-Centered Prototype Design of a Health Care Robot for Treating Type 2 Diabetes in the Community Pharmacy: Development and Usability Study.

JMIR human factors
BACKGROUND: Technology can be an effective tool for providing health services and disease self-management, especially in diabetes care. Technology tools for disease self-management include health-related applications for computers and smartphones as ...

Predicting diabetic retinopathy based on routine laboratory tests by machine learning algorithms.

European journal of medical research
OBJECTIVES: This study aimed to identify risk factors for diabetic retinopathy (DR) and develop machine learning (ML)-based predictive models using routine laboratory data in patients with type 2 diabetes mellitus (T2DM).

Denoised recurrence label-based deep learning for prediction of postoperative recurrence risk and sorafenib response in HCC.

BMC medicine
BACKGROUND: Pathological images of hepatocellular carcinoma (HCC) contain abundant tumor information that can be used to stratify patients. However, the links between histology images and the treatment response have not been fully unveiled.

Does gender matter? The impact of gender and gender match on the relation between destructive leadership and follower outcomes.

BMC psychology
BACKGROUND: Destructive leadership has been linked to negative consequences for both organizations and followers. Research has also shown that leader gender affects follower perceptions of leadership behavior and follower outcomes [1-3]. However, kno...

Interpretable machine learning models for prolonged Emergency Department wait time prediction.

BMC health services research
OBJECTIVE: Prolonged Emergency Department (ED) wait times lead to diminished healthcare quality. Utilizing machine learning (ML) to predict patient wait times could aid in ED operational management. Our aim is to perform a comprehensive analysis of M...

Developing a deep learning model for the automated monitoring of acupuncture needle insertion: enhancing safety in traditional acupuncture practices.

BMC complementary medicine and therapies
BACKGROUND: Acupuncture is a widely practiced traditional therapy, yet safety concerns, particularly needle breakage and retention, remain critical issues that can lead to complications such as infections, organ injury, or chronic pain. This study ai...