Harnessing Artificial Intelligence for Global Health Advancement

Journal of Data Analysis and Information Processing, Год журнала: 2025, Номер 13(01), С. 66 - 78

Опубликована: Янв. 1, 2025

Язык: Английский

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Challenges for Ethics Review Committees in Regulating Medical Artificial Intelligence Research

Indian Journal of Surgical Oncology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 17, 2025

Язык: Английский

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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence

Medicina, Год журнала: 2025, Номер 61(3), С. 433 - 433

Опубликована: Фев. 28, 2025

The integration of artificial intelligence (AI) in ophthalmology is transforming the field, offering new opportunities to enhance diagnostic accuracy, personalize treatment plans, and improve service delivery. This review provides a comprehensive overview current applications future potential AI ophthalmology. algorithms, particularly those utilizing machine learning (ML) deep (DL), have demonstrated remarkable success diagnosing conditions such as diabetic retinopathy (DR), age-related macular degeneration, glaucoma with precision comparable to, or exceeding, human experts. Furthermore, being utilized develop personalized plans by analyzing large datasets predict individual responses therapies, thus optimizing patient outcomes reducing healthcare costs. In surgical applications, AI-driven tools are enhancing procedures like cataract surgery, contributing better recovery times reduced complications. Additionally, AI-powered teleophthalmology services expanding access eye care underserved remote areas, addressing global disparities availability. Despite these advancements, challenges remain, concerning data privacy, security, algorithmic bias. Ensuring robust governance ethical practices crucial for continued conclusion, research should focus on developing sophisticated models capable handling multimodal data, including genetic information histories, provide deeper insights into disease mechanisms responses. Also, collaborative efforts among governments, non-governmental organizations (NGOs), technology companies essential deploy solutions effectively, especially low-resource settings.

Язык: Английский

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Pathology in the artificial intelligence era: Guiding innovation and implementation to preserve human insight

Academic Pathology, Год журнала: 2025, Номер 12(1), С. 100166 - 100166

Опубликована: Янв. 1, 2025

The integration of artificial intelligence in pathology has ignited discussions about the role technology diagnostics-whether serves as a tool for augmentation or risks replacing human expertise. This manuscript explores intelligence's evolving contributions to pathology, emphasizing its potential capacity enhance, rather than eclipse, pathologist's role. Through historical comparisons, such transition from analog digital radiology, this paper highlights how technological advancements have historically expanded professional capabilities without diminishing essential element. Current applications pathology-from diagnostic standardization workflow efficiency-demonstrate augment accuracy, expedite processes, and improve consistency across institutions. However, challenges remain algorithmic bias, regulatory oversight, maintaining interpretive skills among pathologists. discussion underscores importance comprehensive governance frameworks, educational curricula, public engagement initiatives ensure remains collaborative endeavor that empowers professionals, upholds ethical standards, enhances patient outcomes. ultimately advocates balanced approach where expertise work concert advance future medicine.

Язык: Английский

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Artificial intelligence in personalized medicine: transforming diagnosis and treatment

Deleted Journal, Год журнала: 2025, Номер 7(3)

Опубликована: Март 1, 2025

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A Review on Revolutionizing Healthcare Technologies with AI and ML Applications in Pharmaceutical Sciences

Drugs and Drug Candidates, Год журнала: 2025, Номер 4(1), С. 9 - 9

Опубликована: Март 4, 2025

Background/Objectives: The integration of Artificial Intelligence (AI) and Machine Learning (ML) in pharmaceutical research development is transforming the industry by improving efficiency effectiveness across drug discovery, development, healthcare delivery. This review explores diverse applications AI ML, emphasizing their role predictive modeling, repurposing, lead optimization, clinical trials. Additionally, highlights AI’s contributions to regulatory compliance, pharmacovigilance, personalized medicine while addressing ethical considerations. Methods: A comprehensive literature was conducted assess impact ML various domains. Research articles, case studies, reports were analyzed examine AI-driven advancements computational chemistry, trials, safety, supply chain management. Results: have demonstrated significant research, including improved target identification, accelerated discovery through generative models, enhanced structure-based design via molecular docking QSAR modeling. In streamlines patient recruitment, predicts trial outcomes, enables real-time monitoring. maintenance, process inventory management manufacturing chains. Furthermore, has revolutionized enabling precise treatment strategies genomic data analysis, biomarker diagnostics. Conclusions: are reshaping offering innovative solutions care. enhances outcomes operational efficiencies raising challenges that require transparent, accountable applications. Future will rely on collaborative efforts ensure its responsible implementation, ultimately driving continued transformation sector.

Язык: Английский

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Artificial intelligence and public health: prospects, hype and challenges

Public Health Research & Practice, Год журнала: 2025, Номер 35(1)

Опубликована: Март 12, 2025

Objectives and importance of the study Applications artificial intelligence (AI) platforms technologies to healthcare have been widely promoted as offering revolutionary improvements efficiencies in clinical practice health services organisation. Practical applications AI public are now emerging receiving similar attention. This paper provides an overview issues examples research that help separate potential from hype. Methods Selective review analysis cross-section relevant literature. Results Great exists for use research. includes immediate improving education communication directly with public, well great productive generative through chatbots virtual assistants communication. also has disease surveillance science, example epidemic pandemic early warning systems, synthetic data generation, sequential decision-making uncertain conditions (reinforcement learning) risk prediction. Most published examining these other is at a fairly stage, making it difficult probable benefits undoubtedly demonstrating but identifying challenges, quality relevance information being produced by AI; access, trust technology different populations; practical application support science. There real risks current access patterns may exacerbate existing inequities orientation towards personalisation advice divert attention away underlying social economic determinants health. Conclusions Realising not only requires further experimentation careful consideration its ethical implications thoughtful regulation. will ensure advances serve best interests individuals communities worldwide don’t inequalities.

Язык: Английский

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The good, the bad, and the binary

Nursing, Год журнала: 2025, Номер 55(4), С. 26 - 32

Опубликована: Март 24, 2025

Artificial intelligence (AI) promises significant advancements in patient care, burden reduction, and nursing efficiency. This article examines the multifaceted impact of AI on practice; its benefits potential ethical issues; ways for nurses to get involved development, implementation, evaluation.

Язык: Английский

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Artificial Intelligence-Powered Digital Twin Predictive Analytics Model for Smart Healthcare System

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 271 - 324

Опубликована: Март 28, 2025

Health monitoring systems and healthcare organizations produce vast amounts of complicated data, which present opportunities for creative research in medical decision-making. These data capture advances have opened unthinkable domains AI digital twin-related applications. AI-powered twin supports process automation, real-time health monitoring, enhanced decision-making, personalized healthcare, predictive analytics. applications can create models that mimic human physiology using various advanced computing approaches. The potential twins be used to advance better outcomes. Hence, this chapter aims provide an Artificial Intelligence-powered analytics model innovative system. Integrating into the smart field improve procedures, treatment, a intelligent ecosystem.

Язык: Английский

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The Role of Artificial Intelligence in Managing Bipolar Disorder: A New Frontier in Patient Care

Journal of Clinical Medicine, Год журнала: 2025, Номер 14(7), С. 2515 - 2515

Опубликована: Апрель 7, 2025

Background/Objectives: Bipolar disorder (BD) is a complex and chronic mental health condition that poses significant challenges for both patients healthcare providers. Traditional treatment methods, including medication therapy, remain vital, but there increasing interest in the application of artificial intelligence (AI) to enhance BD management. AI has potential improve mood episode prediction, personalize plans, provide real-time support, offering new opportunities managing more effectively. Our primary objective was explore role transforming management BD, specifically tracking, personalized regimens. Methods: To management, we conducted review recent literature using key search terms. We included studies discussed applications personalization. The were selected based on their relevance AI's with attention PICO criteria: Population-individuals diagnosed BD; Intervention-AI tools personalization, support; Comparison-traditional methods (when available); Outcome-measures effectiveness, improvements patient care. Results: findings from research reveal promising developments use Studies suggest AI-powered can enable proactive care, improving outcomes reducing burden professionals. ability analyze data wearable devices, smartphones, even social media platforms provides valuable insights early detection dynamic adjustments. Conclusions: While still its stages, it presents transformative However, further development are crucial fully realize supporting optimizing efficacy.

Язык: Английский

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