Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy

Seminars in Cancer Biology, Journal Year: 2023, Volume and Issue: 90, P. 57 - 72

Published: Feb. 14, 2023

Language: Английский

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Analyzing Barriers and Enablers for the Acceptance of Artificial Intelligence Innovations into Radiology Practice: A Scoping Review

Tomography, Journal Year: 2023, Volume and Issue: 9(4), P. 1443 - 1455

Published: July 28, 2023

Objectives: This scoping review was conducted to determine the barriers and enablers associated with acceptance of artificial intelligence/machine learning (AI/ML)-enabled innovations into radiology practice from a physician’s perspective. Methods: A systematic search performed using Ovid Medline Embase. Keywords were used generate refined queries inclusion computer-aided diagnosis, intelligence, enablers. Three reviewers assessed articles, fourth reviewer for disagreements. The risk bias mitigated by including both quantitative qualitative studies. Results: An electronic January 2000 2023 identified 513 Twelve articles found fulfill criteria: studies (n = 4), survey 7), randomized controlled trials (RCT) 1). Among most common AI implementation radiologists’ lack trust in innovations; awareness, knowledge, familiarity technology; perceived threat professional autonomy radiologists. important high expectations AI’s potential added value; decrease errors diagnosis; increase efficiency when reaching improve quality patient care. Conclusions: that few have been designed specifically identify practice. majority perception replacing radiologists, rather than other or adoption AI. To comprehensively evaluate advantages disadvantages integrating practice, gathering more robust research evidence on stakeholder perspectives attitudes is essential.

Language: Английский

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

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: March 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.

Language: Английский

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Review of Personalized Medicine and Pharmacogenomics of Anti-Cancer Compounds and Natural Products

Genes, Journal Year: 2024, Volume and Issue: 15(4), P. 468 - 468

Published: April 8, 2024

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These have improved precision of treatment and reduced adverse effects side effects. Personalized therapy is a prominent hot topic current medicine also represents future direction development. With continuous advancements in gene sequencing high-throughput screening, research development strategies personalized developed rapidly. This review elaborates strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, computation-aided drug design. technologies rely on molecular classification diseases, global signaling network within organisms, new models all targets, significantly support medicine. Meanwhile, we summarize drugs, such as lorlatinib, osimertinib, other natural products, deliver therapeutic based genetic mutations. highlights potential challenges interpreting mutations combining while providing ideas pharmacogenomics cancer study.

Language: Английский

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Detection and classification of mandibular fractures in panoramic radiography using artificial intelligence

Dentomaxillofacial Radiology, Journal Year: 2024, Volume and Issue: 53(6), P. 363 - 371

Published: April 23, 2024

This study evaluated the performance of YOLOv5 deep learning model in detecting different mandibular fracture types panoramic images.

Language: Английский

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