Heliyon, Journal Year: 2025, Volume and Issue: 11(3), P. e42054 - e42054
Published: Jan. 18, 2025
Hepatocellular carcinoma (HCC) is a primary liver cancer that originates from underlying inflammation, often associated with Hepatitis B virus (HBV) or C (HCV) infections. Despite the availability of treatments, there are high rates tumour relapse due to development drug resistance in infected cells. Next-Generation Sequencing (NGS) plays crucial role overcoming this issue by sequencing both viral and host genomes identify mutations genetic heterogeneity. The knowledge gained then utilised develop countermeasures against these mutants through different combination therapies. Advances NGS have led higher accuracy throughput, thereby enabling personalized effective treatments. purpose article highlight how has contributed precision medicine HCC possible integration artificial intelligence (AI) bolster advancement.
Language: Английский
Citations
1Machine learning in ocular oncology and oculoplasty: Transforming diagnosis and treatment
IP International Journal of Ocular Oncology and Oculoplasty, Journal Year: 2025, Volume and Issue: 10(4), P. 196 - 207
Published: Jan. 14, 2025
In the domains of ocular oncology and oculoplasty, machine learning (ML) has become a game-changing technology, providing previously unheard-of levels precision in diagnosis, treatment planning, outcome prediction. Using imaging modalities, genomic data, clinical characteristics, this chapter investigates integration algorithms detection tumours, including retinoblastoma uveal melanoma. Through predictive modelling real-time decision-making, it also emphasises how ML might improve surgical outcomes orbital reconstruction eyelid correction. Automated examination fundus photographs, histological slides, 3D been made possible by methods like deep natural language processing, which have improved individualised therapeutic approaches decreased diagnostic errors. Additionally, use augmented reality robotics surgery is significant development oculoplasty. Notwithstanding its potential, issues data heterogeneity, algorithm interpretability, ethical considerations are roadblocks that need to be addressed. This explores cutting-edge developments, real-world uses, potential future paths, offering researchers doctors thorough resource. Dipali Vikas Mane, Associate Professor, Shriram Shikshan Sanstha’s College Pharmacy, Paniv-413113
Language: Английский
Citations
0Using The Cancer Genome Atlas from cBioPortal to Develop Genomic Datasets for Machine Learning Assisted Cancer Treatment
bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 22, 2025
Abstract Predicting the impact of genetic mutations is crucial for understanding diseases like cancer. Polymorphism Phenotyping (PolyPhen) and Sorting Intolerant From Tolerant (SIFT) are key tools assessing how amino acid substitutions affect protein function mutation pathogenicity. To our knowledge, no ready-to-use genomic dataset exists prediction models to identify potentially harmful mutations, which could support research clinical decisions. This study develops non-genomic datasets using The Cancer Genome Atlas (TCGA) from cBioPortal applies machine learning predict PolyPhen SIFT scores. We explore three classification models: Random Forest (RF), Extreme Gradient Boosting (XGBoost), an ensemble RF-XGBoost model. Experimental results show that data yields more accurate predictions than data. model performs best on data, achieving average accuracies 88.43% 95.13% SIFT, highlighting potential artificial intelligence in analysis disease treatment.
Language: Английский
Citations
0The Role of AI-Based Chatbots in Public Health Emergencies: A Narrative Review
Future Internet, Journal Year: 2025, Volume and Issue: 17(4), P. 145 - 145
Published: March 26, 2025
The rapid emergence of infectious disease outbreaks has underscored the urgent need for effective communication tools to manage public health crises. Artificial Intelligence (AI)-based chatbots have become increasingly important in these situations, serving as critical resources provide immediate and reliable information. This review examines role AI-based emergencies, particularly during outbreaks. By providing real-time responses inquiries, help disseminate accurate information, correct misinformation, reduce anxiety. Furthermore, AI play a vital supporting healthcare systems by triaging offering guidance on symptoms preventive measures, directing users appropriate services. not only enhances access information but also helps alleviate workload professionals, allowing them focus more complex tasks. However, implementation is without challenges. Issues such accuracy user trust, ethical considerations regarding data privacy are factors that be addressed optimize their effectiveness. Additionally, adaptability rapidly evolving scenarios essential sustained relevance. Despite challenges, potential AI-driven transform emergencies significant. highlights importance continuous development integration into strategies enhance preparedness response efforts Their accessible, accurate, timely makes indispensable modern emergency management.
Language: Английский
Citations
0Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs
Cancers, Journal Year: 2024, Volume and Issue: 16(22), P. 3884 - 3884
Published: Nov. 20, 2024
The integration of AI has revolutionized cancer drug development, transforming the landscape discovery through sophisticated computational techniques. AI-powered models and algorithms have enhanced computer-aided design (CADD), offering unprecedented precision in identifying potential anticancer compounds. Traditionally, been a complex, resource-intensive process, but introduces new opportunities to accelerate discovery, reduce costs, optimize efficiency. This manuscript delves into transformative applications AI-driven methodologies predicting developing drugs, critically evaluating their reshape future therapeutics while addressing challenges limitations.
Language: Английский
Citations
3Artificial Intelligence for Public Health
Published: Jan. 1, 2025
Language: Английский
Citations
0