AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Implications of large language models such as ChatGPT for dental medicine.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
OBJECTIVE: This article provides an overview of the implications of ChatGPT and other large language models (LLMs) for dental medicine.

Deep learning for the early identification of periodontitis: a retrospective, multicentre study.

Clinical radiology
AIM: To develop a deep-learning model to help general dental practitioners diagnose periodontitis accurately and at an early stage.

Dental Caries Detection and Classification in CBCT Images Using Deep Learning.

International dental journal
OBJECTIVES: This study aimed to investigate the accuracy of deep learning algorithms to diagnose tooth caries and classify the extension and location of dental caries in cone beam computed tomography (CBCT) images. To the best of our knowledge, this ...

Evaluation of the Performance of Generative AI Large Language Models ChatGPT, Google Bard, and Microsoft Bing Chat in Supporting Evidence-Based Dentistry: Comparative Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: The increasing application of generative artificial intelligence large language models (LLMs) in various fields, including dentistry, raises questions about their accuracy.

Advocating for population health: The role of public health practitioners in the age of artificial intelligence.

Canadian journal of public health = Revue canadienne de sante publique
Over the past decade, artificial intelligence (AI) has begun to transform Canadian organizations, driven by the promise of improved efficiency, better decision-making, and enhanced client experience. While AI holds great opportunities, there are also...

Development and evaluation of a model to identify publications on the clinical impact of pharmacist interventions.

Research in social & administrative pharmacy : RSAP
BACKGROUND: Pharmacists are increasingly involved in patient care. Pharmacy practice research helps them identify the most clinically meaningful interventions. However, the lack of a widely accepted controlled vocabulary in this field hinders the dis...

Enhancing pharmacist intervention targeting based on patient clustering with unsupervised machine learning.

Expert review of pharmacoeconomics & outcomes research
OBJECTIVES: Adherence to the American Diabetes Association (ADA) Standards of Medical Care is low. This study aimed to assist pharmacists in identifying patients for diabetes control interventions using unsupervised machine learning.

[Not Available].

Recenti progressi in medicina
This study explores the potential use of ChatGPT, an AI-based language model, in assessing herbal-drug interactions (HDi) to enhance clinical decision-making. HDi can pose significant health risks by reducing drug efficacy or causing unwanted side ef...

Impact of a clinical pharmacist-led, artificial intelligence-supported medication adherence program on medication adherence performance, chronic disease control measures, and cost savings.

Journal of the American Pharmacists Association : JAPhA
BACKGROUND: Chronic diseases are the leading cause of disability and death in the United States. Clinical pharmacists have been shown to optimize health outcomes and reduce health care expenditures in patients with chronic diseases through improving ...