Evaluation of risk of bias in neuroimaging-based artificial intelligence models for psychiatric diagnosis: a systematic review
Z Chen, X Liu, Q Yang, YJ Wang, K Miao… - JAMA network …, 2023 - jamanetwork.com
Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review
Artificial intelligence (AI) has been successfully exploited in diagnosing many mental
disorders. Numerous systematic reviews summarize the evidence on the accuracy of AI …
disorders. Numerous systematic reviews summarize the evidence on the accuracy of AI …
Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …
mental disorder is recognized as a significant breakthrough in the field of psychiatry …
Predicting the future of neuroimaging predictive models in mental health
Predictive modeling using neuroimaging data has the potential to improve our
understanding of the neurobiology underlying psychiatric disorders and putatively …
understanding of the neurobiology underlying psychiatric disorders and putatively …
[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review
R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting
Advances in artificial intelligence have cultivated a strong interest in developing and
validating the clinical utilities of computer-aided diagnostic models. Machine learning for …
validating the clinical utilities of computer-aided diagnostic models. Machine learning for …
Artificial intelligence applications in psychoradiology
One important challenge in psychiatric research is to translate findings from brain imaging
research studies that identified brain alterations in patient groups into an accurate diagnosis …
research studies that identified brain alterations in patient groups into an accurate diagnosis …
Artificial intelligence for mental health care: clinical applications, barriers, facilitators, and artificial wisdom
Artificial intelligence (AI) is increasingly employed in health care fields such as oncology,
radiology, and dermatology. However, the use of AI in mental health care and …
radiology, and dermatology. However, the use of AI in mental health care and …
The clinical added value of imaging: a perspective from outcome prediction
Objective measures of psychiatric health would be of benefit in clinical practice. Despite
considerable research in the area of psychiatric neuroimaging outcome prediction …
considerable research in the area of psychiatric neuroimaging outcome prediction …
Expectations for artificial intelligence (AI) in psychiatry
Abstract Purpose of Review Artificial intelligence (AI) is often presented as a transformative
technology for clinical medicine even though the current technology maturity of AI is low. The …
technology for clinical medicine even though the current technology maturity of AI is low. The …