AI Medical Compendium Topic:
Case-Control Studies

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Incorporating computer vision on smart phone photographs into screening for inflammatory arthritis: results from an Indian patient cohort.

Rheumatology (Oxford, England)
OBJECTIVES: Convolutional neural networks (CNNs) are increasingly used to classify medical images, but few studies utilize smartphone photographs. The objective of this study was to assess CNNs for differentiating patients from controls and detecting...

Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data.

Cancer reports (Hoboken, N.J.)
BACKGROUND: Breast cancer (BC) is a major global health concern with rising incidence and mortality rates in many developing countries. Effective BC risk assessment models are crucial for prevention and early detection. While the Gail model, a tradit...

Deep learning in the precise assessment of primary Sjögren's syndrome based on ultrasound images.

Rheumatology (Oxford, England)
OBJECTIVES: This study aimed to investigate the value of a deep learning (DL) model based on greyscale ultrasound (US) images for precise assessment and accurate diagnosis of primary Sjögren's syndrome (pSS).

Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes.

World journal of gastroenterology
BACKGROUND: Insulin resistance, lipotoxicity, and mitochondrial dysfunction contribute to the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD). Mitochondrial dysfunction impairs oxidative phosphorylation and increases ...

The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals.

The Journal of the Acoustical Society of America
Vocal intensity is quantified by sound pressure level (SPL). The SPL can be measured by either using a sound level meter or by comparing the energy of the recorded speech signal with the energy of the recorded calibration tone of a known SPL. Neither...

Machine learning and metabolomics identify biomarkers associated with the disease extent of ulcerative colitis.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Ulcerative colitis (UC) is a metabolism-related chronic intestinal inflammatory disease. Disease extent is a key parameter of UC. Using serum metabolic profiling to identify noninvasive biomarkers of disease extent may inform the...

Unveiling the Immune Landscape of Delirium through Single-Cell RNA Sequencing and Machine Learning: Towards Precision Diagnosis and Therapy.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Postoperative delirium (POD) poses significant clinical challenges regarding its diagnosis and treatment. Identifying biomarkers that can predict and diagnose POD is crucial for improving patient outcomes.

Using machine learning to predict patients with polycystic ovary disease in Chinese women.

Taiwanese journal of obstetrics & gynecology
OBJECTIVE: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used tradit...

Forme fruste keratoconus detection with OCT corneal topography using artificial intelligence algorithms.

Journal of cataract and refractive surgery
PURPOSE: To differentiate a normal cornea from a forme fruste keratoconus (FFKC) with the swept-source optical coherence tomography (SS-OCT) topography CASIA 2 using machine learning artificial intelligence algorithms.