Prevention of medical errors

Brain tumor intelligent diagnosis based on Auto-Encoder and U-Net feature extraction.

Preoperative classification of brain tumors is critical to developing personalized treatment plans, however existing classification methods rely on manual intervention and often have problems with efficiency and accuracy, which may lead to misdiagnosis or delayed diagnosis in clinical practice and affect the therapeutic effect. We propose a fully automated approach to brain tumor magnetic resonanc...

Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.

Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate t...

Using aggregated AI detector outcomes to eliminate false positives in STEM-student writing.

Generative artificial intelligence (AI) large language models have become sufficiently accessible and user-friendly to assist students with course wor...

Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study.

BACKGROUND: Cervical cancer remains a major global health issue. Personalized, data-driven cervical cancer prevention (CCP) strategies tailored to phe...

Improving readability of shoulder and elbow surgery online patient education material with Chat GPT (Chat Generative Pretrained Transformer) 4.

BACKGROUND: Health literacy is crucial for effective doctor-patient communication, particularly for surgical patients who need to comprehend complex p...

Innovative hand pose based sign language recognition using hybrid metaheuristic optimization algorithms with deep learning model for hearing impaired persons.

Sign language (SL) is an effective mode of communication, which uses visual-physical methods like hand signals, expressions, and body actions to commu...

Pyramid Network With Quality-Aware Contrastive Loss for Retinal Image Quality Assessment.

Captured retinal images vary greatly in quality. Low-quality images increase the risk of misdiagnosis. This motivates to design effective retinal imag...

Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models.

Orthognathic surgery, or corrective jaw surgery, is performed to correct severe dentofacial deformities and is increasingly sought for cosmetic purpos...

Deep learning and robotics enabled approach for audio based emotional pragmatics deficits identification in social communication disorders.

The aim of this study is to develop Deep Learning (DL) enabled robotic systems to identify audio-based emotional pragmatics deficits in individuals wi...

LLM services in the management of social communications.

This paper proposes enhancing social communication management with a behavioral economics approach through artificial intelligence instruments. The re...

Enhanced personalized prediction of baseball-related upper extremity injuries through novel features and explainable artificial intelligence.

Upper extremity injuries in baseball players demand advanced prevention. Our study analyzed clinical features using machine learning techniques to pro...

Enhancing Patient-Physician Communication: Simulating African American Vernacular English in Medical Diagnostics with Large Language Models.

UNLABELLED: Effective communication is crucial in reducing health disparities. However, linguistic differences, such as African American Vernacular En...

Nano biosensor unlocks tumor derived immune signals for the early detection of ovarian cancer.

Ovarian cancer is a critical health issue for women nowadays. Its impact is significant because of its high mortality rate (324,603 worldwide), late-s...

Hand X-rays findings and a disease screening for Turner syndrome through deep learning model.

BACKGROUND: Turner syndrome (TS) is one of the important causes of short stature in girls, but there are cases of misdiagnosis and missed diagnosis in...

Health Communication on the Internet: Promoting Public Health and Exploring Disparities in the Generative AI Era.

Health communication and promotion on the internet have evolved over time, driven by the development of new technologies, including generative artific...

Initial study of verbal and nonverbal communication training through the collaborative operation of a humanoid robot for individuals with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) experience difficulties in both verbal and nonverbal communication. Collaborative work allows them to ...

Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.

PURPOSE: Gastrointestinal (GI) dilatations are frequently observed in radiographs of pediatric patients who visit emergency departments with acute sym...

Communication-Efficient Hybrid Federated Learning for E-Health With Horizontal and Vertical Data Partitioning.

Electronic healthcare (e-health) allows smart devices and medical institutions to collaboratively collect patients' data, which is trained by artifici...

Enhancing Slip, Trip, and Fall Prevention: Real-World Near-Fall Detection with Advanced Machine Learning Technique.

Slips, trips, and falls (STFs) are a major occupational hazard that contributes significantly to workplace injuries and the associated financial costs...

Study on the prediction performance of AIDS monthly incidence in Xinjiang based on time series and deep learning models.

OBJECTIVE: AIDS is a highly fatal infectious disease of Class B, and Xinjiang is a high-incidence region for AIDS in China. The core of prevention and...