AIMC Topic: Pilot Projects
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Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study.
Frontiers in public health
Jan 15, 2025
OBJECTIVE: Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.
Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial.
Journal of medical Internet research
Jan 14, 2025
BACKGROUND: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment meth...
Exploring artificial intelligence for differentiating early syphilis from other skin lesions: a pilot study.
BMC infectious diseases
Jan 8, 2025
BACKGROUND: Early diagnosis of syphilis is vital for its effective control. This study aimed to develop an Artificial Intelligence (AI) diagnostic model based on radiomics technology to distinguish early syphilis from other clinical skin lesions.
AI-assisted digital video analysis reveals changes in gait among three-day event horses during competition.
Journal of equine veterinary science
Jan 6, 2025
The value and welfare of performance horses is closely tied to locomotor behaviors, but we lack objective and quantitative measures for these characteristics, and qualitative approaches for assessing gait do not provide measures suitable for large-sc...
Diagnosis of approximal caries in children with convolutional neural networks based detection algorithms on radiographs: A pilot study.
Acta odontologica Scandinavica
Jan 6, 2025
OBJECTIVES: Approximal caries diagnosis in children is difficult, and artificial intelligence-based research in pediatric dentistry is scarce. To create a convolutional neural network (CNN)-based diagnostic system for the prompt and efficient identif...
Ascertaining provider-level implicit bias in electronic health records with rules-based natural language processing: A pilot study in the case of prostate cancer.
PloS one
Dec 30, 2024
PURPOSE: Implicit, unconscious biases in medicine are personal attitudes about race, ethnicity, gender, and other characteristics that may lead to discriminatory patterns of care. However, there is no consensus on whether implicit bias represents a t...
AI-Enhanced Healthcare: Integrating ChatGPT-4 in ePROs for Improved Oncology Care and Decision-Making: A Pilot Evaluation.
Current oncology (Toronto, Ont.)
Dec 26, 2024
BACKGROUND: Since 2023, ChatGPT-4 has been impactful across several sectors including healthcare, where it aids in medical information analysis and education. Electronic patient-reported outcomes (ePROs) play a crucial role in monitoring cancer patie...
A clinical pilot trial of an artificial intelligence-driven smart phone application of bowel preparation for colonoscopy: a randomized clinical trial.
Scandinavian journal of gastroenterology
Dec 22, 2024
BACKGROUND: High-quality bowel preparation is paramount for a successful colonoscopy. This study aimed to explore the effect of artificial intelligence-driven smartphone software on the quality of bowel preparation.
A pilot study for speech assessment to detect the severity of Parkinson's disease: An ensemble approach.
Computers in biology and medicine
Dec 21, 2024
BACKGROUND: Changes in voice are a symptom of Parkinson's disease and used to assess the progression of the condition. However, natural differences in the voices of people can make this challenging. Computerized binary speech classification can ident...
A Bias Network Approach (BNA) to Encourage Ethical Reflection Among AI Developers.
Science and engineering ethics
Dec 17, 2024
We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI developers to identify, map, and relate biases across the AI development process. This approach addresses the limitations of what we call the "isolationist approach to AI ...
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