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Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.
BMC medical imaging
Jan 13, 2025
BACKGROUND: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. L...
Artificial intelligence-enhanced diagnosis of degenerative joint disease using temporomandibular joint panoramic radiography and joint noise data.
Scientific reports
Jan 13, 2025
This study aimed to develop an artificial intelligence (AI) model for the screening of degenerative joint disease (DJD) using temporomandibular joint (TMJ) panoramic radiography and joint noise data. A total of 2631 TMJ panoramic images were collecte...
Assessment of hard tissue changes after horizontal guided bone regeneration with the aid of deep learning CBCT segmentation.
Clinical oral investigations
Jan 13, 2025
OBJECTIVES: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.
Exploring the influence of age on the causes of death in advanced nasopharyngeal carcinoma patients undergoing chemoradiotherapy using machine learning methods.
Scientific reports
Jan 13, 2025
The present study analyzed the impact of age on the causes of death (CODs) in patients with nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy (CRT) using machine learning approaches. A total of 2841 patients (1037 classified as older, ≥ 60 ...
Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.
Frontiers in cellular and infection microbiology
Jan 13, 2025
INTRODUCTION: This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis.
Golgi protein 73: charting new territories in diagnosing significant fibrosis in MASLD: a prospective cross-sectional study.
Frontiers in endocrinology
Jan 13, 2025
OBJECTIVES: To explore the correlation between serum Golgi protein 73 (GP73) levels and the degree of fibrosis in Metabolic dysfunction associated steatotic liver disease (MASLD); to establish a non-invasive diagnostic algorithm based on serum GP73 a...
Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database.
Frontiers in public health
Jan 13, 2025
BACKGROUND AND AIM: Changes in cognitive function are commonly associated with aging in patients with cardiovascular diseases. The objective of this research was to construct and validate a nomogram-based predictive model for the identification of co...
The use of a ChatGPT-4-based chatbot in teledermatology: A retrospective exploratory study.
Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG
Jan 12, 2025
BACKGROUND AND OBJECTIVES: Integration of artificial intelligence in healthcare, particularly ChatGPT, is transforming medical diagnostics and may benefit teledermatology. This exploratory study compared image description and differential diagnosis g...
Integrated multi-omics analysis identifies a machine learning-derived signature for predicting prognosis and therapeutic vulnerability in clear cell renal cell carcinoma.
Life sciences
Jan 12, 2025
AIMS: Clear cell renal cell carcinoma (ccRCC) shows considerable variation within and between tumors, presents varying treatment responses among patients, possibly due to molecular distinctions. This study utilized a multi-center and multi-omics anal...
Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning.
Sensors (Basel, Switzerland)
Jan 12, 2025
Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diagnosis and treatment rates remain low due to its diverse and often overlapping clinical manifestations. In this context, electroencephalography (EEG) h...
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