InfoScience Trends, Journal Year: 2025, Volume and Issue: 2(5), P. 23 - 32
Published: May 1, 2025
Language: Английский
Diagnostics, Journal Year: 2025, Volume and Issue: 15(3), P. 397 - 397
Published: Feb. 6, 2025
Radioimmunotherapy (RIT) is a novel cancer treatment that combines radiotherapy and immunotherapy to precisely target tumor antigens using monoclonal antibodies conjugated with radioactive isotopes. This approach offers personalized, systemic, durable treatment, making it effective in cancers resistant conventional therapies. Advances artificial intelligence (AI) present opportunities enhance RIT by improving precision, efficiency, personalization. AI plays critical role patient selection, planning, dosimetry, response assessment, while also contributing drug design classification. review explores the integration of into RIT, emphasizing its potential optimize entire process advance personalized care.
Language: Английский
Citations
3
Bioengineering, Journal Year: 2024, Volume and Issue: 11(12), P. 1267 - 1267
Published: Dec. 13, 2024
Artificial intelligence (AI) is an area of computer science that focuses on designing machines or systems can perform operations would typically need human intelligence. AI a rapidly developing technology has grabbed the interest researchers from all across globe in healthcare industry. Advancements machine learning and data analysis have revolutionized oral health diagnosis, treatment, management, making it transformative force healthcare, particularly dentistry. Particularly dentistry, becoming increasingly prevalent as contributes to diagnosis oro-facial diseases, offers treatment modalities, manages practice dental operatory. All disciplines, including medicine, operative pediatric periodontology, orthodontics, maxillofacial surgery, prosthodontics, forensic odontology, adopted AI. The majority applications dentistry are for diagnoses based radiographic optical images, while other tasks less applicable due constraints such availability, uniformity, computational power. Evidence-based considered gold standard decision by professionals, models learn expertise. Dentistry provide numerous benefits, improved accuracy increased administrative task efficiency. Dental practices already implementing various applications, imaging planning, robotics automation, augmented virtual reality, predictive analytics, support. field extensively used artificial assist less-skilled practitioners reaching more precise diagnosis. These effectively recognize classify patients with problems into different risk categories, both individually group basis. objective this descriptive review most recent developments
Language: Английский
Citations
5
Algorithms, Journal Year: 2025, Volume and Issue: 18(2), P. 96 - 96
Published: Feb. 8, 2025
Computer vision and artificial intelligence have revolutionized the field of pathological image analysis, enabling faster more accurate diagnostic classification. Deep learning architectures like convolutional neural networks (CNNs), shown superior performance in tasks such as classification, segmentation, object detection pathology. has significantly improved accuracy disease diagnosis healthcare. By leveraging advanced algorithms machine techniques, computer systems can analyze medical images with high precision, often matching or even surpassing human expert performance. In pathology, deep models been trained on large datasets annotated pathology to perform cancer diagnosis, grading, prognostication. While approaches show great promise challenges remain, including issues related model interpretability, reliability, generalization across diverse patient populations imaging settings.
Language: Английский
Citations
0
Bratislavské lekárske listy/Bratislava medical journal, Journal Year: 2025, Volume and Issue: unknown
Published: March 13, 2025
Abstract Artificial intelligence is rapidly reshaping medical research, education, and clinical practice. This brief communication reviews new AI applications—from personalized learning immersive simulations in education to AI-assisted diagnostics settings—and examines the accompanying ethical practical challenges. Drawing on insights from last November’s editorial Bratislava Medical Journal, paper argues that while offers powerful tools, human oversight remains essential. Future efforts must establish clear governance frameworks update educational curricula foster effective human–machine collaboration, ensuring uniquely elements of science creativity endure.
Language: Английский
Citations
0
InfoScience Trends, Journal Year: 2025, Volume and Issue: 2(5), P. 23 - 32
Published: May 1, 2025
Language: Английский
Citations
0