AIMC Topic: Middle Aged

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Hierarchical random forest model, inflammation and oxidative stress as predictors of the atherogenic index of plasma and diabetes progression.

Scientific reports
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that increases the risk of cardiovascular complications. The atherogenic index of plasma (AIP) is a risk marker for T2DM and cardiovascular disease on the basis of lipid profiles. T2DM an...

Deep phenotyping of patient lived experience in functional bowel disorders using machine learning.

Scientific reports
Contemporary clinical management relies on a diagnostic label as the primary guide to treatment. However, individual patients' lived experiences vary more widely than standard diagnostic categories reflect. This is especially true for functional bowe...

Preoperative prediction of lymph node metastasis risk in papillary thyroid carcinoma based on multiple model comparisons.

Scientific reports
The clinical necessity of lymph node dissection in papillary thyroid carcinoma (PTC) surgery remains contentious. This study compared four logistic regression (LR) models (with distinct feature selection strategies) and four machine learning (ML) mod...

Artificial Intelligence Driven Diagnosis and Prognosis Comparison of ChatGPT-4o and DeepSeek-R1 in HIV Negative Talaromycosis.

Mycopathologia
This study evaluates and compares the diagnostic and prognostic capabilities of ChatGPT-4o and DeepSeek-R1 in 56 HIV-negative talaromycosis cases. Clinical case fragments were de-identified and submitted to both models, with diagnostic accuracy and p...

Impact of the oxidative balance score on cardiovascular-kidney-metabolic syndrome: A cross-sectional study with machine learning prediction.

PloS one
BACKGROUND AND AIM: The antioxidant diet and lifestyle are widely believed to prevent and even treat various diseases; however, their applicability to cardiovascular-kidney-metabolic (CKM) syndrome remains unknown. In this study, the correlation betw...

A novel potential biomarker panel to diagnose depression derived from big proteomic data.

Journal of affective disorders
BACKGROUND: There is still no clinical biomarker to diagnose depression. Given the complexity of a multifactorial disease like depression, a single biomarker is unlikely to capture the full heterogeneity of the disease and be applicable in clinical p...

Artificial intelligence-assisted endoscopic diagnosis system for diagnosing Helicobacter pylori infection: a multicenter study.

BMC medicine
BACKGROUND: Deep learning algorithm-based artificial intelligence (AI) has significantly advanced the domain of endoscopic diagnosis; however, its utilization for detecting Helicobacter pylori (H. pylori) infections remains constrained. We aimed to d...

Development and validation of an age estimation model based on dental characteristics using panoramic radiographs.

Scientific reports
Dental characteristics have considerable potential as indicators for estimating chronological age. This study developed a regression model for age estimation using dental characteristics observed in panoramic radiographs. A total of 2,391 radiographs...

Development and validation of a machine learning model integrating BUN/Cr ratio for mortality prediction in critically ill atrial fibrillation patients.

Scientific reports
Atrial fibrillation (AF), the most prevalent critical care arrhythmia, demonstrates substantial mortality associations where renal dysfunction management plays a pivotal therapeutic role. We examined the prognostic capacity of admission blood urea ni...