AIMC Topic: Artificial Intelligence

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The Role of Artificial Intelligence and Texture Analysis in Interventional Radiological Treatments of Liver Masses: A Narrative Review.

Critical reviews in oncogenesis
Liver lesions, including both benign and malignant tumors, pose significant challenges in interventional radiological treatment planning and prognostication. The emerging field of artificial intelligence (AI) and its integration with texture analysis...

Adoption of AI in Oncological Imaging: Ethical, Regulatory, and Medical-Legal Challenges.

Critical reviews in oncogenesis
Artificial Intelligence (AI) algorithms have shown great promise in oncological imaging, outperforming or matching radiologists in retrospective studies, signifying their potential for advanced screening capabilities. These AI tools offer valuable su...

Exploring the Potential of Artificial Intelligence in Breast Ultrasound.

Critical reviews in oncogenesis
Breast ultrasound has emerged as a valuable imaging modality in the detection and characterization of breast lesions, particularly in women with dense breast tissue or contraindications for mammography. Within this framework, artificial intelligence ...

Artificial Intelligence in Lung Cancer Imaging: From Data to Therapy.

Critical reviews in oncogenesis
Lung cancer remains a global health challenge, leading to substantial morbidity and mortality. While prevention and early detection strategies have improved, the need for precise diagnosis, prognosis, and treatment remains crucial. In this comprehens...

Artificial Intelligence-Based Counting Algorithm Enables Accurate and Detailed Analysis of the Broad Spectrum of Spot Morphologies Observed in Antigen-Specific B-Cell ELISPOT and FluoroSpot Assays.

Methods in molecular biology (Clifton, N.J.)
Antigen-specific B-cell ELISPOT and multicolor FluoroSpot assays, in which the membrane-bound antigen itself serves as the capture reagent for the antibodies that B cells secrete, inherently result in a broad range of spot sizes and intensities. The ...

Automatic detection of thyroid nodules with a real-time artificial intelligence system in a real clinical scenario and the associated influencing factors.

Clinical hemorheology and microcirculation
BACKGROUND: At present, most articles mainly focused on the diagnosis of thyroid nodules by using artificial intelligence (AI), and there was little research on the detection performance of AI in thyroid nodules.

Ombuds AI.

Healthcare quarterly (Toronto, Ont.)
The integration of artificial intelligence (AI) offers the promise of developing open-source frameworks and tools that incorporate social and behavioural determinants of health data, thereby fostering an empirical understanding of the causal factors ...

From the Editors.

Healthcare quarterly (Toronto, Ont.)
There is no doubt that 2023 was a very difficult year for many Canadians, as well as people across the world. War caused massive upheaval globally, inflation continued to impose financial hardship on families and our health systems experienced anothe...

Chapter 9. Return to the revision of the bioethics law regarding the use of artificial intelligence in the field of medical imaging.

Journal international de bioethique et d'ethique des sciences
On the occasion of the sixth AI international Summit (November 22-24, 2023), Professor Daniel Rueckert (Technical University of Munich) replies to our questions on ethical issues raised by the use of artificial intelligence in medical imaging.