AIMC Topic: Feasibility Studies
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A feasibility study of lung tumor segmentation on kilo-voltage radiographic images with transfer learning: Toward tumor motion tracking in radiotherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Mar 1, 2025
PURPOSE: To segment the lung tumor on kilo-voltage X-ray radiographic images acquired during treatment toward the markerless lung tumor tracking.
Radiotherapy dose prediction using off-the-shelf segmentation networks: A feasibility study with GammaPod planning.
Medical physics
Feb 28, 2025
BACKGROUND: Radiotherapy requires precise, patient-specific treatment planning to achieve high-quality dose distributions that improve patient outcomes. Traditional manual planning is time-consuming and clinically impractical for performing necessary...
The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations.
BMC cancer
Feb 25, 2025
BACKGROUND: Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibil...
The feasibility of using generative artificial intelligence for history taking in virtual patients.
BMC research notes
Feb 24, 2025
OBJECTIVE: This study aimed to design and develop a virtual patient program using generative Artificial Intelligence (AI) technology, providing medical students opportunities to practice history-taking with a chatbot. We evaluated the feasibility of ...
The Feasibility of Large Language Models in Verbal Comprehension Assessment: Mixed Methods Feasibility Study.
JMIR formative research
Feb 24, 2025
BACKGROUND: Cognitive assessment is an important component of applied psychology, but limited access and high costs make these evaluations challenging.
Feasibility study of texture-based machine learning approach for early detection of neonatal jaundice.
Scientific reports
Feb 22, 2025
Untreated neonatal jaundice can have severe consequences. Effective screening for neonatal jaundice can prevent long-term complications in infants. Non-invasive approaches may be beneficial in settings with limited resources. This feasibility study e...
Artificial intelligence assessment of tissue-dissection efficiency in laparoscopic colorectal surgery.
Langenbeck's archives of surgery
Feb 22, 2025
PURPOSE: Several surgical-skill assessment tools emphasize the importance of efficient tissue-dissection, whose assessment relies on human judgment and is thus subject to bias. Automated assessment may help solve this problem. This study aimed to ver...
Integrating blockchain technology with artificial intelligence for the diagnosis of tibial plateau fractures.
European journal of trauma and emergency surgery : official publication of the European Trauma Society
Feb 21, 2025
PURPOSE: The application of artificial intelligence (AI) in healthcare has seen widespread implementation, with numerous studies highlighting the development of robust algorithms. However, limited attention has been given to the secure utilization of...
Automated quantification of brain PET in PET/CT using deep learning-based CT-to-MR translation: a feasibility study.
European journal of nuclear medicine and molecular imaging
Feb 18, 2025
PURPOSE: Quantitative analysis of PET images in brain PET/CT relies on MRI-derived regions of interest (ROIs). However, the pairs of PET/CT and MR images are not always available, and their alignment is challenging if their acquisition times differ c...
Large Language Models-Supported Thrombectomy Decision-Making in Acute Ischemic Stroke Based on Radiology Reports: Feasibility Qualitative Study.
Journal of medical Internet research
Feb 13, 2025
BACKGROUND: The latest advancement of artificial intelligence (AI) is generative pretrained transformer large language models (LLMs). They have been trained on massive amounts of text, enabling humanlike and semantical responses to text-based inputs ...
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