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Automation

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PICOT questions and search strategies formulation: A novel approach using artificial intelligence automation.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
AIM: The aim of this study was to evaluate and compare artificial intelligence (AI)-based large language models (LLMs) (ChatGPT-3.5, Bing, and Bard) with human-based formulations in generating relevant clinical queries, using comprehensive methodolog...

Automated workflow for the cell cycle analysis of (non-)adherent cells using a machine learning approach.

eLife
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study...

HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate measurement of the hip-knee-ankle (HKA) angle is essential for informed clinical decision-making in the management of knee osteoarthritis (OA). Knee OA is commonly associated with varus deformity, where the alignment of the knee ...

Decision-making of autonomous vehicles in interactions with jaywalkers: A risk-aware deep reinforcement learning approach.

Accident; analysis and prevention
Jaywalking, as a hazardous crossing behavior, leaves little time for drivers to anticipate and respond promptly, resulting in high crossing risks. The prevalence of Autonomous Vehicle (AV) technologies has offered new solutions for mitigating jaywalk...

Automatic AI tool for opportunistic screening of vertebral compression fractures on chest frontal radiographs: A multicenter study.

Bone
Vertebral compression fractures (VCFs) are the most common type of osteoporotic fractures, yet they are often clinically silent and undiagnosed. Chest frontal radiographs (CFRs) are frequently used in clinical practice and a portion of VCFs can be de...

Tunable and real-time automatic interventional x-ray collimation from semi-supervised deep feature extraction.

Medical physics
BACKGROUND: The use of endovascular procedures is becoming increasingly popular across multiple clinical domains. These procedures are generally performed under image guidance using an interventional c-arm x-ray system. Radiation exposure to both pat...

Automatic segmentation of pericardial adipose tissue from cardiac MR images via semi-supervised method with difference-guided consistency.

Medical physics
BACKGROUND: Accurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high co...

Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).

Physics in medicine and biology
To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-ris...

BD-StableNet: a deep stable learning model with an automatic lesion area detection function for predicting malignancy in BI-RADS category 3-4A lesions.

Physics in medicine and biology
The latest developments combining deep learning technology and medical image data have attracted wide attention and provide efficient noninvasive methods for the early diagnosis of breast cancer. The success of this task often depends on a large amou...