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Where medical statistics meets artificial intelligence
Where Medical Statistics Meets Artificial Intelligence | New England Journal of Medicine Skip to
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main content The New England Journal of Medicine homepage Advanced Search SEARCH …
A survey of large language models in medicine: Progress, application, and challenge
Large language models (LLMs), such as ChatGPT, have received substantial attention due
to their capabilities for understanding and generating human language. While there has …
to their capabilities for understanding and generating human language. While there has …
Blinded, randomized trial of sonographer versus AI cardiac function assessment
Artificial intelligence (AI) has been developed for echocardiography,–, although it has not yet
been tested with blinding and randomization. Here we designed a blinded, randomized non …
been tested with blinding and randomization. Here we designed a blinded, randomized non …
Guiding principles to address the impact of algorithm bias on racial and ethnic disparities in health and health care
MH Chin, N Afsar-Manesh, AS Bierman… - JAMA Network …, 2023 - jamanetwork.com
Importance Health care algorithms are used for diagnosis, treatment, prognosis, risk
stratification, and allocation of resources. Bias in the development and use of algorithms can …
stratification, and allocation of resources. Bias in the development and use of algorithms can …
[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …
reporting by providing evidence-based recommendations for the minimum set of items to be …
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review
Skin cancers occur commonly worldwide. The prognosis and disease burden are highly
dependent on the cancer type and disease stage at diagnosis. We systematically reviewed …
dependent on the cancer type and disease stage at diagnosis. We systematically reviewed …
Ethical machine learning in healthcare
The use of machine learning (ML) in healthcare raises numerous ethical concerns,
especially as models can amplify existing health inequities. Here, we outline ethical …
especially as models can amplify existing health inequities. Here, we outline ethical …
Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review
Artificial intelligence (AI) promises to change health care, with some studies showing proof
of concept of a provider-level performance in various medical specialties. However, there …
of concept of a provider-level performance in various medical specialties. However, there …
[HTML][HTML] Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …