AI Medical Compendium Topic

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Medicine

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Artificial Intelligence in pathology: current applications, limitations, and future directions.

Irish journal of medical science
PURPOSE: Given AI's recent success in computer vision applications, majority of pathologists anticipate that it will be able to assist them with a variety of digital pathology activities. Massive improvements in deep learning have enabled a synergy b...

[Big hype about ChapGPT in medicine : Is it something for rhythmologists? What must be taken into consideration?].

Herzschrittmachertherapie & Elektrophysiologie
ChatGPT, a chatbot based on a large language model, is currently attracting much attention. Modern machine learning (ML) architectures enable the program to answer almost any question, to summarize, translate, and even generate its own texts, all in ...

The role of artificial intelligence in the future of urogynecology.

International urogynecology journal
Artificial intelligence (AI) in medicine is a rapidly growing field aimed at using machine learning models to improve health outcomes and patient experiences. Many new platforms have become accessible and therefore it seems inevitable that we conside...

Large language models in medicine.

Nature medicine
Large language models (LLMs) can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare settings. ChatGPT is a generative artificial intelligence (AI) chat...

Large language models encode clinical knowledge.

Nature
Large language models (LLMs) have demonstrated impressive capabilities, but the bar for clinical applications is high. Attempts to assess the clinical knowledge of models typically rely on automated evaluations based on limited benchmarks. Here, to a...

Algorithmic fairness in artificial intelligence for medicine and healthcare.

Nature biomedical engineering
In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how pat...

Introducing medical students to deep learning through image labelling: a new approach to meet calls for greater artificial intelligence fluency among medical trainees.

Canadian medical education journal
Our approach addresses the urgent need for AI experience for the doctors of tomorrow. Through a medical education-focused approach to data labelling, we have fostered medical student competence in medical imaging and AI. We envision our framework bei...

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations.

Computers in biology and medicine
The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detect...

[Digitalization in rehabilitation].

Orthopadie (Heidelberg, Germany)
BACKGROUND: The term digitalization is in trend. In addition to modernizing existing structures and converting analogue to digital processes, there are now a large number of digital applications available in the medical field. This is also increasing...