The Impact of Advanced Neural Network Architectures for Extracting Elusive Information DOI

Renu Kachhoria,

Love Mittal,

Prakash Divakaran

et al.

Published: Dec. 29, 2023

Advanced Neural community Architectures, consisting of Convolution Networks (CNNs), have emerged as powerful solutions to demanding situations in extracting complicated and elusive information from large, high-dimensional datasets. CNNs effective feature extraction abilities that may be used identify subtle patterns, traits, relationships those but, architectures must tailored the particular nature hassle allows you maximize potential these fashions. were effectively some domain names discover styles facts could otherwise remain hidden. As an example, been inside medical quickly accurately become aware cardiologic patterns electrocardiograms. Similarly, they within security perceive capability threats earlier than occur. In each names, extract cognitive numerous datasets speedy appropriately has saved lives avoided failures. The exercise use superior neural permit statistics is complex requires thoughtful layout. structure recall traits project, which include records kind, range dimensions concerned, amount noise or outliers, determine strategies are maximum suitable for every specific utility.

Language: Английский

Empowering personalized pharmacogenomics with generative AI solutions DOI
Mullai Murugan, Bo Yuan, Eric Venner

et al.

Journal of the American Medical Informatics Association, Journal Year: 2024, Volume and Issue: 31(6), P. 1356 - 1366

Published: March 6, 2024

Abstract Objective This study evaluates an AI assistant developed using OpenAI’s GPT-4 for interpreting pharmacogenomic (PGx) testing results, aiming to improve decision-making and knowledge sharing in clinical genetics enhance patient care with equitable access. Materials Methods The employs retrieval-augmented generation (RAG), which combines retrieval generative techniques, by harnessing a base (KB) that comprises data from the Clinical Pharmacogenetics Implementation Consortium (CPIC). It uses context-aware generate tailored responses user queries this KB, further refined through prompt engineering guardrails. Results Evaluated against specialized PGx question catalog, showed high efficacy addressing queries. Compared ChatGPT 3.5, it demonstrated better performance, especially provider-specific requiring citations. Key areas improvement include enhancing accuracy, relevancy, representative language responses. Discussion integration of RAG significantly enhanced assistant’s utility. RAG’s ability incorporate domain-specific CPIC data, including recent literature, proved beneficial. Challenges persist, such as need genetic/PGx models accuracy relevancy ethical, regulatory, safety concerns. Conclusion underscores AI’s potential transforming healthcare provider support accessibility complex information. While careful implementation large like is necessary, clear they can substantially understanding data. With development, these tools could augment expertise, productivity, delivery equitable, patient-centered services.

Language: Английский

Citations

23
Invasion and metastasis in cancer: molecular insights and therapeutic targets DOI Creative Commons

Yongxing Li,

Fengshuo Liu,

Qingjin Cai

et al.

Signal Transduction and Targeted Therapy, Journal Year: 2025, Volume and Issue: 10(1)

Published: Feb. 20, 2025

The progression of malignant tumors leads to the development secondary in various organs, including bones, brain, liver, and lungs. This metastatic process severely impacts prognosis patients, significantly affecting their quality life survival rates. Research efforts have consistently focused on intricate mechanisms underlying this corresponding clinical management strategies. Consequently, a comprehensive understanding biological foundations tumor metastasis, identification pivotal signaling pathways, systematic evaluation existing emerging therapeutic strategies are paramount enhancing overall diagnostic treatment capabilities for tumors. However, current research is primarily metastasis within specific cancer types, leaving significant gaps our complex cascade, organ-specific tropism mechanisms, targeted treatments. In study, we examine sequential processes elucidate driving organ-tropic systematically analyze tumors, those tailored organ involvement. Subsequently, synthesize most recent advances technologies challenges opportunities encountered pertaining bone metastasis. Our objective offer insights that can inform future practice crucial field.

Language: Английский

Citations

3
Strategies of Artificial intelligence tools in the domain of nanomedicine DOI

Mohammad Habeeb,

Huay Woon You, Mutheeswaran Umapathi

et al.

Journal of Drug Delivery Science and Technology, Journal Year: 2023, Volume and Issue: 91, P. 105157 - 105157

Published: Nov. 10, 2023

Language: Английский

Citations

28
Artificial intelligence in oncology: ensuring safe and effective integration of language models in clinical practice DOI Creative Commons
Loïc Verlingue,

C Boyer,

Louise Olgiati

et al.

The Lancet Regional Health - Europe, Journal Year: 2024, Volume and Issue: 46, P. 101064 - 101064

Published: Sept. 6, 2024

Language: Английский

Citations

6
Epithelial–mesenchymal transition to Mitigate Age-Related Progression in Lung Cancer DOI
Riya Thapa,

Saurabh Gupta,

Gaurav Gupta

et al.

Ageing Research Reviews, Journal Year: 2024, Volume and Issue: 102, P. 102576 - 102576

Published: Nov. 7, 2024

Language: Английский

Citations

6
Molecular dynamics simulations for the structure-based drug design: targeting small-GTPases proteins DOI
Angela Parise,

Sofia Cresca,

Alessandra Magistrato

et al.

Expert Opinion on Drug Discovery, Journal Year: 2024, Volume and Issue: 19(10), P. 1259 - 1279

Published: Aug. 6, 2024

Molecular Dynamics (MD) simulations can support mechanism-based drug design. Indeed, MD by capturing biomolecule motions at finite temperatures reveal hidden binding sites, accurately predict drug-binding poses, and estimate the thermodynamics kinetics, crucial information for discovery campaigns. Small-Guanosine Triphosphate Phosphohydrolases (GTPases) regulate a cascade of signaling events, that affect most cellular processes. Their deregulation is linked to several diseases, making them appealing targets. The broad roles small-GTPases in processes recent approval covalent KRas inhibitor as an anticancer agent renewed interest targeting small-GTPase with small molecules.

Language: Английский

Citations

4
Mass Spectrometry‐Based Proteomics for Next‐Generation Precision Oncology DOI
Kuen‐Tyng Lin, Gul Muneer, Peirong Huang

et al.

Mass Spectrometry Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

ABSTRACT Cancer is the leading cause of death worldwide characterized by patient heterogeneity and complex tumor microenvironment. While genomics‐based testing has transformed modern medicine, challenge diverse clinical outcomes highlights unmet needs for precision oncology. As functional molecules regulating cellular processes, proteins hold great promise as biomarkers drug targets. Mass spectrometry (MS)‐based proteomics illuminated molecular features cancers facilitated discovery or therapeutic targets, paving way innovative strategies that enhance personalized treatment. In this article, we introduced tools current achievements MS‐based proteomics, choice targeted MS from to validation phases, profiling sensitivity bulk samples single‐cell level tissue liquid biopsy specimens, regulatory landscape protein laboratory‐developed tests (LDTs). The challenges, success future perspectives in translating research assay into applications are also discussed. With well‐designed studies demonstrate benefits meet requirements both analytical performance, assays promising with numerous opportunities improve cancer diagnosis, treatment, monitoring.

Language: Английский

Citations

0
A Machine Learning Approach Using [18F]FDG PET-Based Radiomics for Prediction of Tumor Grade and Prognosis in Pancreatic Neuroendocrine Tumor DOI
Yongjin Park, Young Suk Park,

Seung Tae Kim

et al.

Molecular Imaging and Biology, Journal Year: 2023, Volume and Issue: 25(5), P. 897 - 910

Published: July 3, 2023

Language: Английский

Citations

10
Possible integration of artificial intelligence with photodynamic therapy and diagnosis: A review DOI Creative Commons
Nkune Williams Nkune, Heidi Abrahamse

Journal of Drug Delivery Science and Technology, Journal Year: 2024, Volume and Issue: 101, P. 106210 - 106210

Published: Sept. 16, 2024

Language: Английский

Citations

3
Mechanism-aware and multimodal AI: beyond model-agnostic interpretation DOI Creative Commons
Annalisa Occhipinti, Suraj Verma, Le Minh Thao Doan

et al.

Trends in Cell Biology, Journal Year: 2023, Volume and Issue: 34(2), P. 85 - 89

Published: Dec. 11, 2023

Artificial intelligence (AI) is widely used for exploiting multimodal biomedical data, with increasingly accurate predictions and model-agnostic interpretations, which are however also agnostic to biological mechanisms. Combining metabolic modelling, 'omics, imaging data via AI can generate that be interpreted mechanistically transparently, therefore significantly higher therapeutic potential.

Language: Английский

Citations

7