Revista Portuguesa de Psiquiatria e Saúde Mental, Год журнала: 2024, Номер 10(2), С. 35 - 37
Опубликована: Дек. 29, 2024
Nature reviews. Cancer, Год журнала: 2024, Номер 24(6), С. 427 - 441
Опубликована: Май 16, 2024
Язык: Английский
Процитировано
64
Pharmaceutics, Год журнала: 2024, Номер 16(10), С. 1328 - 1328
Опубликована: Окт. 14, 2024
Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep and other advanced computational methods. These innovations unlocked unprecedented opportunities the acceleration drug discovery delivery, optimization treatment regimens, improvement patient outcomes. AI is swiftly transforming industry, revolutionizing everything from development to personalized medicine, target identification validation, selection excipients, prediction synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While integration promises enhance efficiency, reduce costs, improve both medicines health, it also raises important questions regulatory point view. In this review article, we will present comprehensive overview AI's applications in covering areas such as discovery, safety, more. By analyzing current research trends case studies, aim shed light on transformative impact industry its broader implications healthcare.
Язык: Английский
Процитировано
37
The Lancet Digital Health, Год журнала: 2024, Номер 6(9), С. e662 - e672
Опубликована: Авг. 23, 2024
Among the rapid integration of artificial intelligence in clinical settings, large language models (LLMs), such as Generative Pre-trained Transformer-4, have emerged multifaceted tools that potential for health-care delivery, diagnosis, and patient care. However, deployment LLMs raises substantial regulatory safety concerns. Due to their high output variability, poor inherent explainability, risk so-called AI hallucinations, LLM-based applications serve a medical purpose face challenges approval devices under US EU laws, including recently passed Artificial Intelligence Act. Despite unaddressed risks patients, misdiagnosis unverified advice, are available on market. The ambiguity surrounding these creates an urgent need frameworks accommodate unique capabilities limitations. Alongside development frameworks, existing regulations should be enforced. If regulators fear enforcing market dominated by supply or technology companies, consequences layperson harm will force belated action, damaging potentiality advice.
Язык: Английский
Процитировано
26
npj Digital Medicine, Год журнала: 2024, Номер 7(1)
Опубликована: Май 22, 2024
On 13 March 2024, the much-anticipated AI Act was passed by EU parliament and will soon be adopted as law. It apply new requirements for developers deployers of AI-enabled digital health tools (DHTs), including a defined class high-risk systems general-purpose AI. Although text law is available, complete in all but final checks legal wording much still not known about how affect landscape beyond. The many aspects ambiguous, often high-level objectives are stated, with detail to come later associated guidance, standards, member state policy. also uncertain intersect pre-existing sector-specific legislation medical There future steps legislative process that can clarify ambiguity, guidelines, implementing laws, author remains optimistic get implementation right.
Язык: Английский
Процитировано
21
Nature Reviews Gastroenterology & Hepatology, Год журнала: 2024, Номер 21(8), С. 585 - 599
Опубликована: Апрель 16, 2024
Язык: Английский
Процитировано
12
Current Oncology, Год журнала: 2024, Номер 31(9), С. 5255 - 5290
Опубликована: Сен. 6, 2024
Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning natural language processing, their applications HNC. The integration of with imaging techniques, genomics, electronic health records explored, emphasizing its role early detection, biomarker discovery, planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, real-time monitoring systems are poised to further advance field. Addressing these fostering among experts, clinicians, researchers crucial developing equitable effective applications. future HNC holds significant promise, offering potential breakthroughs diagnostics, personalized therapies, improved patient outcomes.
Язык: Английский
Процитировано
7
npj Precision Oncology, Год журнала: 2024, Номер 8(1)
Опубликована: Окт. 23, 2024
Large language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, compare methodological approaches outcomes. includes 34 studies. primarily evaluated on their ability answer oncologic questions across The highlights a significant variance, influenced by diverse methodologies evaluation criteria. Furthermore, differences inherent model capabilities, prompting strategies, oncological subdomains contribute heterogeneity. lack use standardized LLM-specific reporting protocols leads disparities, which must be addressed ensure comparability LLM ultimately leverage reliable integration technologies into practice.
Язык: Английский
Процитировано
6
Frontiers in Immunology, Год журнала: 2024, Номер 15
Опубликована: Сен. 5, 2024
Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of hematologic malignancies, offering remarkable remission rates in otherwise refractory conditions. However, its expansion into broader oncological applications faces significant hurdles, including limited efficacy solid tumors, safety concerns related to toxicity, and logistical challenges manufacturing scalability. This review critically examines latest advancements aimed at overcoming these obstacles, highlighting innovations CAR engineering, novel targeting strategies, improvements delivery persistence within tumor microenvironment. We also discuss development allogeneic T cells as off-the-shelf therapies, strategies mitigate adverse effects, integration with other therapeutic modalities. comprehensive analysis underscores synergistic potential enhance safety, efficacy, accessibility providing a forward-looking perspective on their evolutionary trajectory cancer treatment.
Язык: Английский
Процитировано
5
JHEP Reports, Год журнала: 2024, Номер 6(12), С. 101209 - 101209
Опубликована: Сен. 6, 2024
Язык: Английский
Процитировано
4
Deleted Journal, Год журнала: 2025, Номер unknown
Опубликована: Фев. 17, 2025
Процитировано
0