AIMC Topic: Reproducibility of Results
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Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip.
BMC musculoskeletal disorders
Nov 13, 2024
OBJECTIVES: Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radio...
ChatGPT for parents' education about early childhood caries: A friend or foe?
International journal of paediatric dentistry
Nov 12, 2024
BACKGROUND: With the increasing popularity of online sources for health information, parents may seek information related to early childhood caries (ECC) from artificial intelligence-based chatbots.
Accuracy of 7 Artificial Intelligence-Based Intraocular Lens Power Calculation Formulas in Extremely Long Caucasian Eyes.
American journal of ophthalmology
Nov 12, 2024
PURPOSE: To compare 7 artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in extremely long eyes.
Female
Reproducibility of Results
Aged
Aged, 80 and over
Humans
Artificial Intelligence
Retrospective Studies
Visual Acuity
White People
Phacoemulsification
Biometry
Optics and Photonics
Male
Middle Aged
Refraction, Ocular
Lenses, Intraocular
Axial Length, Eye
Lens Implantation, Intraocular
Myopia, Degenerative
Developing physics-informed neural networks for model predictive control of periodic counter-current chromatography.
Journal of chromatography. A
Nov 12, 2024
The applications of continuous manufacturing technology in biopharmaceuticals require advanced design, monitoring, and control due to its complexity. Traditional mechanistic models, which rely on numerical solutions, suffer from long computational ti...
Diagnostic performance of an artificial intelligence model for the detection of pneumothorax at chest X-ray.
Clinical imaging
Nov 12, 2024
PURPOSE: Pneumothorax (PTX) is a common clinical urgency, its diagnosis is usually performed on chest radiography (CXR), and it presents a setting where artificial intelligence (AI) methods could find terrain in aiding radiologists in facing increasi...
Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.
Genes
Nov 12, 2024
Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. The anoikis-related prognostic signature (ANRS) was gene...
Female
Reproducibility of Results
Aged
Proportional Hazards Models
Gene Expression Profiling
Tumor Microenvironment
Anoikis
Breast Neoplasms
Transcriptome
Drug Screening Assays, Antitumor
Biomarkers, Tumor
Machine Learning
Real-Time Polymerase Chain Reaction
Gene Expression
Enzyme-Linked Immunosorbent Assay
Prognosis
Middle Aged
Reverse Transcriptase Polymerase Chain Reaction
Treatment Outcome
Immunotherapy
Databases, Genetic
Blotting, Western
Antineoplastic Agents
Predictive Value of Tests
Imatinib Mesylate
A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers.
BMC medical imaging
Nov 12, 2024
BACKGROUND: Speckle tracking echocardiography (STE) provides quantification of left ventricular (LV) deformation and is useful in the assessment of LV function. STE is increasingly being used clinically, and every effort to simplify and standardize S...
Exploring the potential of large language models in identifying metabolic dysfunction-associated steatotic liver disease: A comparative study of non-invasive tests and artificial intelligence-generated responses.
Liver international : official journal of the International Association for the Study of the Liver
Nov 11, 2024
BACKGROUND AND AIMS: This study sought to assess the capabilities of large language models (LLMs) in identifying clinically significant metabolic dysfunction-associated steatotic liver disease (MASLD).
Modification and Validation of the System Causability Scale Using AI-Based Therapeutic Recommendations for Urological Cancer Patients: A Basis for the Development of a Prospective Comparative Study.
Current oncology (Toronto, Ont.)
Nov 11, 2024
The integration of artificial intelligence, particularly Large Language Models (LLMs), has the potential to significantly enhance therapeutic decision-making in clinical oncology. Initial studies across various disciplines have demonstrated that LLM-...
Test-Retest Reliability and Responsiveness of the Machine Learning-Based Short-Form of the Berg Balance Scale in Persons With Stroke.
Archives of physical medicine and rehabilitation
Nov 9, 2024
OBJECTIVE: To examine the test-retest reliability, responsiveness, and clinical utility of the machine learning-based short form of the Berg Balance Scale (BBS-ML) in persons with stroke.
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