Artificial Intelligence in Pediatric Epilepsy Detection: Balancing Effectiveness With Ethical Considerations for Welfare DOI Creative Commons
Marina Ramzy Mourid, Hamza Irfan, Malik Olatunde Oduoye

и другие.

Health Science Reports, Год журнала: 2025, Номер 8(1)

Опубликована: Янв. 1, 2025

ABSTRACT Background and Aim Epilepsy is a major neurological challenge, especially for pediatric populations. It profoundly impacts both developmental progress quality of life in affected children. With the advent artificial intelligence (AI), there's growing interest leveraging its capabilities to improve diagnosis management epilepsy. This review aims assess effectiveness AI epilepsy detection while considering ethical implications surrounding implementation. Methodology A comprehensive systematic was conducted across multiple databases including PubMed, EMBASE, Google Scholar, Scopus, Medline. Search terms encompassed “pediatric epilepsy,” “artificial intelligence,” “machine learning,” “ethical considerations,” “data security.” Publications from past decade were scrutinized methodological rigor, with focus on studies evaluating AI's efficacy management. Results systems have demonstrated strong potential diagnosing monitoring epilepsy, often matching clinical accuracy. For example, AI‐driven decision support achieved 93.4% accuracy diagnosis, closely aligning expert assessments. Specific methods, like EEG‐based detecting interictal discharges, showed high specificity (93.33%–96.67%) sensitivity (76.67%–93.33%), neuroimaging approaches using rs‐fMRI DTI reached up 97.5% identifying microstructural abnormalities. Deep learning models, such as CNN‐LSTM, also enhanced seizure video by capturing subtle movement expression cues. Non‐EEG sensor‐based methods effectively identified nocturnal seizures, offering promising care. However, considerations around privacy, data security, model bias remain crucial responsible integration. Conclusion While holds immense enhance management, transparency, fairness, security must be rigorously addressed. Collaborative efforts among stakeholders are imperative navigate these challenges effectively, ensuring integration optimizing patient outcomes

Язык: Английский

Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications DOI

Pablo Cruz-Gonzalez,

Anxun He,

Eva K. M. Lam

и другие.

Psychological Medicine, Год журнала: 2025, Номер 55

Опубликована: Янв. 1, 2025

Abstract Artificial intelligence (AI) has been recently applied to different mental health illnesses and healthcare domains. This systematic review presents the application of AI in domains diagnosis, monitoring, intervention. A database search (CCTR, CINAHL, PsycINFO, PubMed, Scopus) was conducted from inception February 2024, a total 85 relevant studies were included according preestablished inclusion criteria. The methods most frequently used support vector machine random forest for learning chatbot tools appeared be accurate detecting, classifying, predicting risk conditions as well treatment response monitoring ongoing prognosis disorders. Future directions should focus on developing more diverse robust datasets enhancing transparency interpretability models improve clinical practice.

Язык: Английский

Процитировано

4
A New Era of Dental Care: Harnessing Artificial Intelligence for Better Diagnosis and Treatment DOI Open Access

Aastha Mahesh Batra,

Amit Reche

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 23, 2023

The integration of artificial intelligence (AI) into dental care holds the promise revolutionizing field by enhancing accuracy diagnosis and treatment. This paper explores impact AI in care, with a focus on its applications diagnosis, treatment planning, patient engagement. AI-driven imaging radiography, computer-aided detection conditions, early disease prevention are discussed detail. Moreover, delves how assists personalized planning provides predictive analytics for care. Ethical privacy considerations, including data security, fairness, regulatory aspects, addressed, highlighting need responsible transparent approach to implementation. Finally, underscores potential collaborative partnership between professionals offer best possible patients, making more efficient, patient-centric, effective. advent dentistry presents remarkable opportunity improve oral health outcomes, benefiting both patients healthcare community.

Язык: Английский

Процитировано

42
Clinicians’ Views on Using Artificial Intelligence in Healthcare: Opportunities, Challenges, and Beyond DOI Open Access
Abdullah Alanazi

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Сен. 14, 2023

The healthcare industry has made significant progress in information technology, which improved procedures and brought about advancements clinical care services. This includes gathering crucial data implementing intelligent health management. Artificial Intelligence (AI) the potential to bolster further existing systems, notably electronic records (EHRs). With AI, EHRs can offer more customized adaptable roles for patients. study aims delve into current uses of AI examine obstacles that come with it.In this study, we employed a qualitative methodology purposive sampling select participants. We sought out clinicians who were eager share their professional insights. Our research involved conducting three focus group interviews, each lasting an hour. moderator began session by introducing study's goals assuring participants confidentiality foster collaborative environment. facilitator asked open-ended questions EHR, including its applications, challenges, AI-assisted features.The conducted 26 identified five areas using delivery. These include predictive analysis, decision support visualization, natural language processing (NLP), patient monitoring, mobile future emerging trends. However, hype surrounding fact technology is still early stages pose challenges. Technical limitations related context-specific reasoning must be addressed. Furthermore, medico-legal challenges arise when supports or autonomously delivers Governments develop strategies ensure AI's responsible transparent application delivery.AI revolutionize through integration other technologies. several addressed before fully realized. development testing complex EHR systems utilize approached accuracy trustworthiness decision-making treatment. Additionally, there need navigate obligations benefits are equitably distributed.

Язык: Английский

Процитировано

41
Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: A systematic review DOI Creative Commons
Sobhan Moazemi, Sahar Vahdati, Jason Li

и другие.

Frontiers in Medicine, Год журнала: 2023, Номер 10

Опубликована: Март 31, 2023

Artificial intelligence (AI) and machine learning (ML) models continue to evolve the clinical decision support systems (CDSS). However, challenges arise when it comes integration of AI/ML into scenarios. In this systematic review, we followed Preferred Reporting Items for Systematic reviews Meta-Analyses (PRISMA), population, intervention, comparator, outcome, study design (PICOS), medical AI life cycle guidelines investigate studies tools which address AI/ML-based approaches towards (CDS) monitoring cardiovascular patients in intensive care units (ICUs). We further discuss recent advances, pitfalls, future perspectives effective routine practices as were identified elaborated over an extensive selection process state-of-the-art manuscripts.

Язык: Английский

Процитировано

38
Balancing the scale: navigating ethical and practical challenges of artificial intelligence (AI) integration in legal practices DOI Creative Commons
Ammar Zafar

Discover Artificial Intelligence, Год журнала: 2024, Номер 4(1)

Опубликована: Апрель 15, 2024

Abstract The paper explores the integration of artificial intelligence in legal practice, discussing ethical and practical issues that arise how it affects customary procedures. It emphasises shift from labour-intensive practice to technology-enhanced methods, with a focus on intelligence's potential improve access services streamline This discussion importantly highlights challenges introduced by Artificial Intelligence, specific bias transparency. These concerns become particularly paramount context sensitive areas, including but not limited to, child custody disputes, criminal justice, divorce settlements. underscores critical need for maintaining vigilance, advocating developing implementing AI systems characterised profound commitment integrity. approach is vital guarantee fairness uphold transparency across all judicial proceedings. study advocates "human loop" strategy combines human knowledge techniques mitigate biases individualised results ensure functions as complement rather than replacement, concludes emphasising necessity preserving element practices.

Язык: Английский

Процитировано

17
Advancements in Pancreatic Cancer Detection: Integrating Biomarkers, Imaging Technologies, and Machine Learning for Early Diagnosis DOI Open Access

Hisham Daher,

Sneha A Punchayil,

Amro Ahmed Elbeltagi Ismail

и другие.

Cureus, Год журнала: 2024, Номер unknown

Опубликована: Март 20, 2024

Artificial intelligence (AI) has come to play a pivotal role in revolutionizing medical practices, particularly the field of pancreatic cancer detection and management. As leading cause cancer-related deaths, warrants innovative approaches due its typically advanced stage at diagnosis dismal survival rates. Present methods, constrained by limitations accuracy efficiency, underscore necessity for novel solutions. AI-driven methodologies present promising avenues enhancing early prognosis forecasting. Through analysis imaging data, biomarker profiles, clinical information, AI algorithms excel discerning subtle abnormalities indicative with remarkable precision. Moreover, machine learning (ML) facilitate amalgamation diverse data sources optimize patient care. However, despite huge potential, implementation faces various challenges. Issues such as scarcity comprehensive datasets, biases algorithm development, concerns regarding privacy security necessitate thorough scrutiny. While offers immense promise transforming management, ongoing research collaborative efforts are indispensable overcoming technical hurdles ethical dilemmas. This review delves into evolution AI, application detection, challenges considerations inherent integration.

Язык: Английский

Процитировано

14
The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review DOI
Phuvamin Suriyaamporn, Boonnada Pamornpathomkul, Prasopchai Patrojanasophon

и другие.

AAPS PharmSciTech, Год журнала: 2024, Номер 25(6)

Опубликована: Авг. 15, 2024

Язык: Английский

Процитировано

14
AI-Enhanced Healthcare: Not a new Paradigm for Informed Consent DOI Creative Commons
Michal Pruski

Journal of Bioethical Inquiry, Год журнала: 2024, Номер unknown

Опубликована: Фев. 1, 2024

Abstract With the increasing prevalence of artificial intelligence (AI) and other digital technologies in healthcare, ethical debate surrounding their adoption is becoming more prominent. Here I consider issue gaining informed patient consent to AI-enhanced care from vantage point United Kingdom’s National Health Service setting. build my discussion around two claims World Organization: that healthcare services should not be denied individuals who refuse there no precedence seeking care. discus U.K. law relating General Data Protection Regulation show current standards are adequate for then suggest future it may possible guarantee access non-AI-enhanced a similar way how we do offer patients manual alternatives automated processes. Throughout focus on issues choice veracity patient–clinician relationship. Finally, best protect potential harms associated with introduction AI via an overly burdensome process but evaluation regulation technologies.

Язык: Английский

Процитировано

13
From Scalpels to Algorithms: The Risk of Dependence on Artificial Intelligence in Surgery. DOI Creative Commons

Abiodun Adegbesan,

Adewunmi Akingbola, Olusola Aremu

и другие.

Journal of Medicine Surgery and Public Health, Год журнала: 2024, Номер unknown, С. 100140 - 100140

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

11
Opportunities and challenges of traditional Chinese medicine doctors in the era of artificial intelligence DOI Creative Commons
Wenyu Li,

Xiaolei Ge,

Shuai Liu

и другие.

Frontiers in Medicine, Год журнала: 2024, Номер 10

Опубликована: Янв. 11, 2024

With the exponential advancement of artificial intelligence (AI) technology, realm medicine is experiencing a paradigm shift, engendering multitude prospects and trials for healthcare practitioners, encompassing those devoted to practice traditional Chinese (TCM). This study explores evolving landscape TCM practitioners in AI era, emphasizing that while can be helpful, it cannot replace role practitioners. It paramount underscore intrinsic worth human expertise, accentuating merely an instrument. On one hand, AI-enabled tools like intelligent symptom checkers, diagnostic assistance systems, personalized treatment plans augment practitioners' expertise capacity, improving diagnosis accuracy efficacy. AI-empowered collaborations between Western strengthen holistic care. other may disrupt conventional workflow doctor-patient relationships. Maintaining humanistic spirit embracing requires upholding professional ethics establishing appropriate regulations. To leverage retaining essence TCM, need hone analytical skills see as complementary. By highlighting promising applications potential risks this provides strategic insights stakeholders promote integrated development better patient outcomes. proper implementation, become valuable assistant elevate quality.

Язык: Английский

Процитировано

10