Artificial intelligence and Psychiatry: An overview

Ray, Adwitiya; Bhardwaj, Akansha; Malik, Yogender Kumar; Singh, Shipra; Gupta, Rajiv

doi:10.1016/j.ajp.2022.103021

Cited by 66 publications

(23 citation statements)

References 67 publications

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“…129 Novel strategies to monitor and combat social isolation and loneliness include using artificial intelligence, virtual and augmented reality, smart homes, robotic pets and telehealth groups. [130][131][132][133] Further studies are warranted to better understand these new interventions' pros and cons. In this regard, as of January 2023, there are 35 ongoing clinical trials on social isolation and loneliness on https://clini caltr ials.gov.…”

Section: Recommendations and Future Directionsmentioning

confidence: 99%

Social isolation and loneliness: Undervalued risk factors for disease states and mortality

Kanbay

Tanrıöver

Çöpür

et al. 2023

Eur J Clin Investigation

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Social isolation and loneliness are two common but undervalued conditions associated with a poor quality of life, decreased overall health and mortality. In this review, we aim to discuss the health consequences of social isolation and loneliness. We first provide the potential causes of these two conditions. Then, we explain the pathophysiological processes underlying the effects of social isolation and loneliness in disease states. Afterwards, we explain the important associations between these conditions and different non‐communicable diseases, as well as the impact of social isolation and loneliness on health‐related behaviours. Finally, we discuss the current and novel potential management strategies for these conditions. Healthcare professionals who attend to socially isolated and/or lonely patients should be fully competent in these conditions and assess their patients thoroughly to detect and properly understand the effects of isolation and loneliness. Patients should be offered education and treatment alternatives through shared decision‐making. Future studies are needed to understand the underlying mechanisms better and to improve the treatment strategies for both social isolation and loneliness.

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Section: Recommendations and Future Directionsmentioning

confidence: 99%

Social isolation and loneliness: Undervalued risk factors for disease states and mortality

Kanbay

Tanrıöver

Çöpür

et al. 2023

Eur J Clin Investigation

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“…9 There are many potential uses of AI in psychiatry. 10,11 My first experience with AI was 13 years ago, when we conducted a project to distinguish fake suicide notes from genuine ones. 12 AI was more successful in correctly identifying fake notes (78% correctly detected) than senior psychiatric residents (49%) or even faculty (53%).…”

Section: How We Got Here and What's Nextmentioning

confidence: 99%

For artificial intelligence, the future is finally here

Nasrallah¹

2023

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“…It can also detect treatable psychiatric conditions via analysis of affective and anxiety disorders using speech patterns and facial expressions (eg, bipolar disorder, major depression, anxiety spectrum and psychotic disorders, attention deficit hyperactivity disorder, addiction disorders, Tourette’s Syndrome, etc.) 12 , 13 ( Figure 1 ). Deep learning algorithms are highly effective compared to human interpretation in medical subspecialties where pattern recognition plays a dominant role, such as dermatology, hematology, oncology, histopathology, ophthalmology, radiology (eg, programmed image analyses), and neurology (eg, analysis for seizures utilizing electroencephalography).…”

Section: Innovative Technological Advances and Applicationsmentioning

confidence: 99%

“…Therefore, the value proposition of novel technologies must be critically appraised via longitudinal and continuous valuations and patient outcomes in terms of its impact on health and disease management. 13 To mitigate healthcare costs, we must control the “technological imperative”—the overuse of technology because of easy availability without due consideration to disease course or outcomes and irrespective of cost–benefit ratio. 3…”

Section: Caveats and Challengesmentioning

confidence: 99%

Promise and Provisos of Artificial Intelligence and Machine Learning in Healthcare

Bhardwaj¹

2022

JHL

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Artificial Intelligence (AI) and Machine Learning (ML) promise to transform all facets of medicine. Expected changes include more effective clinical triage, enhanced accuracy of diagnostic interpretations, improved therapeutic interventions, augmented workflow algorithms, streamlined data collection and processing, more precise disease prognostication, newer pharmacotherapies, and ameliorated genome interpretation. However, many caveats remain. Reliability of input data, interpretation of output data, data proprietorship, consumer privacy, and liability issues due to potential for data breaches will all have to be addressed. Of equal concern will be decreased human interaction in clinical care, patient satisfaction, affordability, and skepticism regarding cost-benefit. This descriptive literature-based treatise expounds on the promise and provisos associated with the anticipated import of AI and ML into all domains of medicine and healthcare in the very near future.

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Artificial intelligence and Psychiatry: An overview

Cited by 66 publications

References 67 publications

Social isolation and loneliness: Undervalued risk factors for disease states and mortality

Social isolation and loneliness: Undervalued risk factors for disease states and mortality

For artificial intelligence, the future is finally here

Promise and Provisos of Artificial Intelligence and Machine Learning in Healthcare

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