Hasil untuk "Medicine"

Junaid Bajwa, Usman Munir, A. Nori et al.

ABSTRACT Artificial intelligence (AI) is a powerful and disruptive area of computer science, with the potential to fundamentally transform the practice of medicine and the delivery of healthcare. In this review article, we outline recent breakthroughs in the application of AI in healthcare, describe a roadmap to building effective, reliable and safe AI systems, and discuss the possible future direction of AI augmented healthcare systems.

F. Mauvais-Jarvis, N. Merz, P. Barnes et al.

Clinicians can encounter sex and gender disparities in diagnostic and therapeutic responses. These disparities are noted in epidemiology, pathophysiology, clinical manifestations, disease progression, and response to treatment. This Review discusses the fundamental influences of sex and gender as modifiers of the major causes of death and morbidity. We articulate how the genetic, epigenetic, and hormonal influences of biological sex influence physiology and disease, and how the social constructs of gender affect the behaviour of the community, clinicians, and patients in the health-care system and interact with pathobiology. We aim to guide clinicians and researchers to consider sex and gender in their approach to diagnosis, prevention, and treatment of diseases as a necessary and fundamental step towards precision medicine, which will benefit men's and women's health.

Jihoon Kim, B. Koo, J. Knoblich

The historical reliance of biological research on the use of animal models has sometimes made it challenging to address questions that are specific to the understanding of human biology and disease. But with the advent of human organoids — which are stem cell-derived 3D culture systems — it is now possible to re-create the architecture and physiology of human organs in remarkable detail. Human organoids provide unique opportunities for the study of human disease and complement animal models. Human organoids have been used to study infectious diseases, genetic disorders and cancers through the genetic engineering of human stem cells, as well as directly when organoids are generated from patient biopsy samples. This Review discusses the applications, advantages and disadvantages of human organoids as models of development and disease and outlines the challenges that have to be overcome for organoids to be able to substantially reduce the need for animal experiments. Human organoids are valuable models for the study of development and disease and for drug discovery, thus complementing traditional animal models. The generation of organoids from patient biopsy samples has enabled researchers to study, for example, infectious diseases, genetic disorders and cancers. This Review discusses the advantages, disadvantages and future challenges of the use of organoids as models for human biology.

J. He, Sally L. Baxter, Jie Xu et al.

A. Rajkomar, Jeffrey Dean, I. Kohane

Machine Learning in Medicine In this view of the future of medicine, patient–provider interactions are informed and supported by massive amounts of data from interactions with similar patients. The...

J. Clusmann, F. Kolbinger, H. Muti et al.

Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and generate text. LLMs attracted substantial public attention after OpenAI’s ChatGPT was made publicly available in November 2022. LLMs can often answer questions, summarize, paraphrase and translate text on a level that is nearly indistinguishable from human capabilities. The possibility to actively interact with models like ChatGPT makes LLMs attractive tools in various fields, including medicine. While these models have the potential to democratize medical knowledge and facilitate access to healthcare, they could equally distribute misinformation and exacerbate scientific misconduct due to a lack of accountability and transparency. In this article, we provide a systematic and comprehensive overview of the potentials and limitations of LLMs in clinical practice, medical research and medical education.

J. Nolan, C. Sandroni, B. Böttiger et al.

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.

V. Kapur, D. Auckley, S. Chowdhuri et al.

L. Zhao, Hong Zhang, Ning Li et al.

ETHNOPHARMACOLOGICAL RELEVANCE Network pharmacology is a new discipline based on systems biology theory, biological system network analysis, and multi-target drug molecule design specific signal node selection. The mechanism of action of TCM formula has the characteristics of multiple targets and levels. The mechanism is similar to the integrity, systematization and comprehensiveness of network pharmacology, so network pharmacology is suitable for the study of the pharmacological mechanism of Chinese medicine compounds. AIM OF THE STUDY The paper summarizes the present application status and existing problems of network pharmacology in the field of Chinese medicine formula, and formulates the research ideas, up-to-date key technology and application method and strategy of network pharmacology. Its purpose is to provide guidance and reference for using network pharmacology to reveal the modern scientific connotation of Chinese medicine. MATERIALS AND METHODS Literatures in this review were searched in PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, ScienceDirect and Google Scholar using the keywords "traditional Chinese medicine", "Chinese herb medicine" and "network pharmacology". The literature cited in this review dates from 2002 to 2022. RESULTS Using network pharmacology methods to predict the basis and mechanism of pharmacodynamic substances of traditional Chinese medicines has become a trend. CONCLUSION Network pharmacology is a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

Rahul C. Deo, Karsten M. Borgwardt

C. Haug, J. Drazen

Position Stand

Erick Hao-Shu

A. Barabási, N. Gulbahce, J. Loscalzo

Marium Malik, M. Tariq, Maira Kamran et al.

D. C. Blood, O. Radostits, J. Arundel

S. Satya‐Murti

Mateusz Dobosz, Klaudia Arciszewska, A. Bogoń et al.

D. Eisenberg, R. Kessler, C. Foster et al.

J. Massarelli