AIMC Topic: Reproducibility of Results
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Using artificial intelligence to semi-automate trustworthiness assessment of randomized controlled trials: a case study.
Journal of clinical epidemiology
Jan 17, 2025
BACKGROUND AND OBJECTIVE: Randomized controlled trials (RCTs) are the cornerstone of evidence-based medicine. Unfortunately, not all RCTs are based on real data. This serious breach of research integrity compromises the reliability of systematic revi...
The application of design of experiments and artificial neural networks in the evaluation of the impact of acidic conditions on cloud point extraction.
Journal of chromatography. A
Jan 17, 2025
This study aimed to analyze the impact of acidic conditions on the recovery of ciprofloxacin and levofloxacin for cloud point extraction with the Design of Experiments and Artificial Neural Networks. The design included 27 experiments featuring three...
ChatGPT and oral cancer: a study on informational reliability.
BMC oral health
Jan 17, 2025
BACKGROUND: Artificial intelligence (AI) and large language models (LLMs) like ChatGPT have transformed information retrieval, including in healthcare. ChatGPT, trained on diverse datasets, can provide medical advice but faces ethical and accuracy co...
Exploring a new paradigm for serum-accessible component rules of natural medicines using machine learning and development and validation of a direct predictive model.
International journal of pharmaceutics
Jan 16, 2025
In the field of pharmaceutical research, Lipinski's Rule of Five (RO5) was once widely regarded as the prevailing standard for the development of novel drugs. Despite the fact that an increasing number of recently approved drugs no longer adhere to t...
A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications.
PloS one
Jan 15, 2025
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge ...
Exploring the Potential of AI-Assisted Technology in Joint Range-of-Motion Measurements: A Reliability Study.
Medicina (Kaunas, Lithuania)
Jan 14, 2025
: Measuring joint range of motion (ROM) is essential for diagnosing and treating musculoskeletal diseases. However, most clinical measurements are conducted using conventional devices, and their reliability may significantly depend on the tester. Thi...
Validation of a Visual Field Prediction Tool for Glaucoma: A Multicenter Study Involving Patients With Glaucoma in the United Kingdom.
American journal of ophthalmology
Jan 13, 2025
PURPOSE: A previously developed machine-learning approach with Kalman filtering technology accurately predicted the disease trajectory for patients with various glaucoma types and severities using clinical trial data. This study assesses performance ...
Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.
The international journal of cardiovascular imaging
Jan 13, 2025
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...
Middle Aged
Neoplasms
Deep Learning
Predictive Value of Tests
Reproducibility of Results
Aged
Male
Coronary Artery Disease
Automation
Coronary Vessels
Vascular Calcification
Coronary Angiography
Positron Emission Tomography Computed Tomography
Radiographic Image Interpretation, Computer-Assisted
Humans
Retrospective Studies
Female
Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach.
Breast (Edinburgh, Scotland)
Jan 13, 2025
BACKGROUND: Breast adenoid cystic carcinoma (BACC) is a rare subtype of breast cancer that accounts for less than 0.1 % of all cases. This study was designed to assess the efficacy of various treatment approaches for BACC and to create the first web-...
Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder.
BMC medical informatics and decision making
Jan 13, 2025
BACKGROUND: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are not regularly captured in structured scales but may be captured in unstructured clinical notes. Natural language processing (NLP) techniques may be u...
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