Prevention of medical errors

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

: Recent research has focused on exploring the relationships between various factors associated with...

Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study.

BACKGROUND: Identifying high risk factors and predicting lung cancer incidence risk are essential to...

Towards practical and privacy-preserving CNN inference service for cloud-based medical imaging analysis: A homomorphic encryption-based approach.

BACKGROUND AND OBJECTIVE: Cloud-based Deep Learning as a Service (DLaaS) has transformed biomedicine...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent ...

A Deep Learning-Based Approach to Detect Lamina Dura Loss on Periapical Radiographs.

This study aimed to develop a custom artificial intelligence (AI) model for detecting lamina dura (L...

Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications.

The integration of artificial intelligence (AI) into health communication systems has introduced a t...

Commentary: Technological innovations for improved prevention and diagnosis of oral disease.

Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.

INTRODUCTION: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical pr...

AI-generated cancer prevention influencers can target risk groups on social media at low cost.

BACKGROUND: This study explores the potential of Artificial Intelligence (AI)-generated social media...

The promise of AI in healthcare: transforming communication and decision-making for patients.

By addressing communication gaps, the integration of AI tools in healthcare has a greater ability to...

Diagnosing Epilepsy with Normal Interictal EEG Using Dynamic Network Models.

OBJECTIVE: Whereas a scalp electroencephalogram (EEG) is important for diagnosing epilepsy, a single...

A Comprehensive Analysis of a Social Intelligence Dataset and Response Tendencies Between Large Language Models (LLMs) and Humans.

In recent years, advancements in the interaction and collaboration between humans and have garnered ...

An Efficient Acute Lymphoblastic Leukemia Screen Framework Based on Multi-Modal Deep Neural Network.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is a leading cause of death among pediatric malignanc...

Artificial Intelligence-Driven Translation Tools in Intensive Care Units for Enhancing Communication and Research.

UNLABELLED: There is a need to improve communication for patients and relatives who belong to cultur...

Evaluation of a context-aware chatbot using retrieval-augmented generation for answering clinical questions on medication-related osteonecrosis of the jaw.

The potential of large language models (LLMs) in medical applications is significant, and Retrieval-...

Evaluation of Multilingual Simplifications of IR Procedural Reports Using GPT-4.

This study assessed the feasibility of large language models such as GPT-4 (OpenAI, San Francisco, C...

Enhancing prediction of major depressive disorder onset in adolescents: A machine learning approach.

Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolesce...

Improving readability in AI-generated medical information on fragility fractures: the role of prompt wording on ChatGPT's responses.

UNLABELLED: Understanding how the questions used when interacting with chatbots impact the readabili...

Artificial intelligence empowered voice generation for amyotrophic lateral sclerosis patients.

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that can result in a progressive ...

Use of machine learning in occupational risk communication for healthcare workers: protocol for scoping review.

INTRODUCTION: With the development of technology, the use of machine learning (ML), a branch of comp...

Key risk factors of generalized anxiety disorder in adolescents: machine learning study.

Adolescents worldwide are increasingly affected by mental health disorders, with anxiety disorders, ...