Published: April 26, 2025
Language: Английский
Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100099 - 100099
Published: April 17, 2024
Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application mental healthcare is no exception. Hence, this review explores the integration of AI into healthcare, elucidating current trends, ethical considerations, future directions dynamic field. This encompassed recent studies, examples applications, considerations shaping Additionally, regulatory frameworks trends research development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, Google Scholar). The inclusion criteria papers published peer-reviewed journals, conference proceedings, or reputable online databases, that specifically focus on field offer comprehensive overview, analysis, existing literature English language. Current reveal AI's potential, with applications such early detection health disorders, personalized treatment plans, AI-driven virtual therapists. However, these advancements are accompanied by challenges concerning privacy, bias mitigation, preservation human element therapy. Future emphasize need for clear frameworks, transparent validation models, continuous efforts. Integrating therapy represents promising frontier healthcare. While holds potential to revolutionize responsible implementation essential. By addressing thoughtfully, we may effectively utilize enhance accessibility, efficacy, ethicality thereby helping both individuals communities.
Language: Английский
Citations
96
Frontiers in Digital Health, Journal Year: 2024, Volume and Issue: 6
Published: March 18, 2024
The paper reviews the entire spectrum of Artificial Intelligence (AI) in mental health and its positive role health. AI has a huge number promises to offer care this looks at multiple facets same. first defines scope area It then various like machine learning, supervised learning unsupervised other AI. psychiatric disorders neurodegenerative disorders, intellectual disability seizures are discussed along with awareness, diagnosis intervention disorders. emotional regulation impact schizophrenia, autism mood is also highlighted. article discusses limitations based approaches need for be culturally aware, structured flexible algorithms an awareness biases that can arise ethical issues may use visited.
Language: Английский
Citations
51
Risk Management and Healthcare Policy, Journal Year: 2024, Volume and Issue: Volume 17, P. 1339 - 1348
Published: May 1, 2024
Abstract: Mental health is an essential component of the and well-being a person community, it critical for individual, society, socio-economic development any country. healthcare currently in sector transformation era, with emerging technologies such as artificial intelligence (AI) reshaping screening, diagnosis, treatment modalities psychiatric illnesses. The present narrative review aimed at discussing current landscape role AI mental healthcare, including treatment. Furthermore, this attempted to highlight key challenges, limitations, prospects providing based on existing works literature. literature search was obtained from PubMed, Saudi Digital Library (SDL), Google Scholar, Web Science, IEEE Xplore, we included only English-language articles published last five years. Keywords used combination Boolean operators ("AND" "OR") were following: "Artificial intelligence", "Machine learning", Deep "Early diagnosis", "Treatment", "interventions", "ethical consideration", "mental Healthcare". Our revealed that, equipped predictive analytics capabilities, can improve planning by predicting individual's response various interventions. Predictive analytics, which uses historical data formulate preventative interventions, aligns move toward individualized preventive healthcare. In screening diagnostic domains, subset AI, machine learning deep learning, has been proven analyze sets predict patterns associated problems. However, limited studies have evaluated collaboration between professionals delivering these sensitive problems require empathy, human connections, holistic, personalized, multidisciplinary approaches. Ethical issues, cybersecurity, lack diversity, cultural sensitivity, language barriers remain concerns implementing futuristic approach Considering approaches, imperative explore aspects. Therefore, future comparative trials larger sample sizes are warranted evaluate different models across regions fill knowledge gaps. Keywords: intelligence, early interventions
Language: Английский
Citations
24
Cureus, Journal Year: 2024, Volume and Issue: unknown
Published: March 19, 2024
This narrative literature review undertakes a comprehensive examination of the burgeoning field, tracing development artificial intelligence (AI)-powered tools for depression and anxiety detection from level intricate algorithms to practical applications. Delivering essential mental health care services is now significant public priority. In recent years, AI has become game-changer in early identification intervention these pervasive disorders. can potentially empower behavioral healthcare by helping psychiatrists collect objective data on patients' progress tasks. study emphasizes current understanding AI, different types its use multiple disorders, advantages, disadvantages, future potentials. As technology develops digitalization modern era increases, there will be rise application psychiatry; therefore, needed. We searched PubMed, Google Scholar, Science Direct using keywords this. studies electronic records (EHR) with machine learning techniques diagnosing all clinical conditions, roughly 99 publications have been found. Out these, 35 were identified disorders age groups, among them, six utilized EHR sources. By critically analyzing prominent scholarly works, we aim illuminate state this technology, exploring successes, limitations, directions. doing so, hope contribute nuanced AI's potential revolutionize diagnostics pave way further research important domain.
Language: Английский
Citations
19
Issues in Mental Health Nursing, Journal Year: 2023, Volume and Issue: 44(10), P. 1020 - 1034
Published: Oct. 3, 2023
This narrative review explores the transformative impact of Artificial Intelligence (AI) on mental health nursing, particularly in enhancing psychiatric patient care. AI technologies present new strategies for early detection, risk assessment, and improving treatment adherence health. They also facilitate remote monitoring, bridge geographical gaps, support clinical decision-making. The evolution virtual assistants AI-enhanced therapeutic interventions are discussed. These technological advancements reshape nurse-patient interactions while ensuring personalized, efficient, high-quality addresses AI's ethical responsible use emphasizing privacy, data security, balance between human interaction tools. As applications care continue to evolve, this encourages continued innovation advocating implementation, thereby optimally leveraging potential nursing.
Language: Английский
Citations
29
Behavioral Sciences, Journal Year: 2023, Volume and Issue: 13(12), P. 1008 - 1008
Published: Dec. 10, 2023
The onset of the COVID-19 pandemic has led to an increased demand for mental health interventions, with a special focus on digitally assisted ones. Self-regulation describes set meta-skills that enable one take control over his/her and it is recognized as vital indicator well-being. Mindfulness training promising strategy promoting self-regulation, behavioral change, A growing body research outlines smart technologies are ready revolutionize way programs place. Artificial intelligence (AI); extended reality (XR) including virtual (VR), augmented (AR), mixed (MR); well advancements in brain computer interfaces (BCIs) transform these programs. Mindfulness-based interventions by mental, emotional, regulation seem be crucial yet under-investigated issue. current systematic review paper aims explore whether how can assist mindfulness development self-regulation skills among people at risk issues populations various clinical characteristics. PRISMA 2020 methodology was utilized respond objectives questions using total sixty-six experimental studies met inclusion criteria. results showed supported technologies, AI-based applications, chatbots, coaches, immersive brain-sensing headbands, effectively trainees developing wide range cognitive, skills, leading greater satisfaction their psychological needs, thus wellness. These may provide positive feedback smarter more inclusive environments, needs or disabilities.
Language: Английский
Citations
26
JMIR Mental Health, Journal Year: 2024, Volume and Issue: 11, P. e56529 - e56529
Published: April 23, 2024
Recent breakthroughs in artificial intelligence (AI) language models have elevated the vision of using conversational AI support for mental health, with a growing body literature indicating varying degrees efficacy. In this paper, we ask when, therapy, it will be easier to replace humans and, conversely, what instances, human connection still more valued. We suggest that empathy lies at heart answer question. First, define different aspects and outline potential empathic capabilities versus AI. Next, consider determines when these are needed most both from perspective therapeutic methodology patient objectives. Ultimately, our goal is prompt further investigation dialogue, urging practitioners scholars engaged AI-mediated therapy keep questions considerations mind investigating implementation health.
Language: Английский
Citations
15
Frontiers in Psychology, Journal Year: 2024, Volume and Issue: 15
Published: March 7, 2024
Objective College students are currently grappling with severe mental health challenges, and research on artificial intelligence (AI) related to college health, as a crucial catalyst for promoting psychological well-being, is rapidly advancing. Employing bibliometric methods, this study aim analyze discuss the AI in student health. Methods Publications pertaining were retrieved from Web of Science core database. The distribution publications analyzed gage predominant productivity. Data countries, authors, journal, keywords using VOSViewer, exploring collaboration patterns, disciplinary composition, hotspots trends. Results Spanning 2003 2023, encompassed 1722 publications, revealing notable insights: (1) gradual rise annual reaching its zenith 2022; (2) Journal Affective Disorders Psychiatry Research emerged most productive influential sources field, significant contributions China, United States, their affiliated higher education institutions; (3) primary issues depression anxiety, machine learning having widest range applications; (4) an imperative enhanced international interdisciplinary collaboration; (5) factors influencing applications. Conclusion This provides succinct yet comprehensive overview facilitating nuanced understanding prospective applications Professionals can leverage discern advantages, risks, potential impacts critical field.
Language: Английский
Citations
12
Journal of Affective Disorders, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 1, 2024
Language: Английский
Citations
8
Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 177, P. 108685 - 108685
Published: June 3, 2024
The intersection of Artificial Intelligence (AI) and perinatal mental health research presents promising avenues, yet uncovers significant challenges for innovation. This review explicitly focuses on this multidisciplinary field undertakes a comprehensive exploration existing therein. Through scoping guided by the Preferred Reporting Items Systematic Reviews Meta-Analyses (PRISMA) framework, we searched relevant literature spanning decade (2013-2023) selected fourteen studies our analysis. We first provide an overview main AI techniques their development, including traditional methods across different categories, as well recent emerging in field. Then, through analysis literature, summarize predominant ML adopted applications studies, such identifying risk factors, predicting disorders, voice assistants, Q&A chatbots. also discuss limitations potential that hinder technologies from improving outcomes, suggest several directions future to meet real needs facilitate translation into clinical settings.
Language: Английский
Citations
6