Pitfalls in interpretive applications of artificial intelligence in radiology

S Behzad, SMH Tabatabaei, MY Lu… - American Journal of …, 2024 - ajronline.org
Interpretive artificial intelligence (AI) tools are poised to change the future of radiology.
However, certain pitfalls may pose particular challenges for optimal AI interpretative …

Challenges for augmenting intelligence in cardiac imaging

PP Sengupta, D Dey, RH Davies… - The Lancet Digital …, 2024 - thelancet.com
Artificial Intelligence (AI), through deep learning, has brought automation and predictive
capabilities to cardiac imaging. However, despite considerable investment, tangible health …

[HTML][HTML] A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy

C Hurkmans, JE Bibault, KK Brock, W van Elmpt… - Radiotherapy and …, 2024 - Elsevier
Abstract Background and purpose Artificial Intelligence (AI) models in radiation therapy are
being developed with increasing pace. Despite this, the radiation therapy community has not …

Clinical, cultural, computational, and regulatory considerations to deploy AI in radiology: perspectives of RSNA and MICCAI experts

MG Linguraru, S Bakas, M Aboian… - Radiology: Artificial …, 2024 - pubs.rsna.org
The Radiological Society of North of America (RSNA) and the Medical Image Computing
and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and …

Evaluating human-ai collaboration: A review and methodological framework

G Fragiadakis, C Diou, G Kousiouris… - arxiv preprint arxiv …, 2024 - arxiv.org
The use of artificial intelligence (AI) in working environments with individuals, known as
Human-AI Collaboration (HAIC), has become essential in a variety of domains, boosting …

[HTML][HTML] Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions

TD Pham, MT Teh, D Chatzopoulou, S Holmes… - Current …, 2024 - mdpi.com
Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing
innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This …

Prospective evaluation of artificial intelligence triage of incidental pulmonary emboli on contrast-enhanced CT examinations of the chest or abdomen

CH Savage, AA Elkassem, O Hamki… - American Journal of …, 2024 - ajronline.org
BACKGROUND. Artificial intelligence (AI) algorithms improved detection of incidental
pulmonary embolism (IPE) on contrast-enhanced CT (CECT) examinations in retrospective …

Artificial intelligence-enhanced patient evaluation: bridging art and science

EK Oikonomou, R Khera - European heart journal, 2024 - academic.oup.com
The advent of digital health and artificial intelligence (AI) has promised to revolutionize
clinical care, but real-world patient evaluation has yet to witness transformative changes. As …

Evaluation of Reliability, Repeatability, Robustness, and Confidence of GPT-3.5 and GPT-4 on a Radiology Board–style Examination

S Krishna, N Bhambra, R Bleakney, R Bhayana - Radiology, 2024 - pubs.rsna.org
Background ChatGPT (OpenAI) can pass a text-based radiology board–style examination,
but its stochasticity and confident language when it is incorrect may limit utility. Purpose To …

Potential strength and weakness of artificial intelligence integration in emergency radiology: A review of diagnostic utilizations and applications in patient care …

M Fathi, R Eshraghi, S Behzad, A Tavasol… - Emergency …, 2024 - Springer
Artificial intelligence (AI) and its recent increasing healthcare integration has created both
new opportunities and challenges in the practice of radiology and medical imaging. Recent …