AIMC Topic: Middle Aged

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Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning.

Scientific reports
To decrease the number of chronic kidney disease (CKD), early diagnosis of diabetic kidney disease is required. We performed invariant information clustering (IIC)-based clustering on glomerular images obtained from nephrectomized kidneys of patients...

Artificial intelligence as a transforming factor in motility disorders-automatic detection of motility patterns in high-resolution anorectal manometry.

Scientific reports
High-resolution anorectal manometry (HR-ARM) is the gold standard for anorectal functional disorders' evaluation, despite being limited by its accessibility and complex data analysis. The London Protocol and Classification were developed to standardi...

Merging motoneuron and postural synergies in prosthetic hand design for natural bionic interfacing.

Science robotics
Despite the advances in bionic reconstruction of missing limbs, the control of robotic limbs is still limited and, in most cases, not felt to be as natural by users. In this study, we introduce a control approach that combines robotic design based on...

Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.

Journal of neurology
BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis o...

Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm Detection-the Tromsø Study.

Neuroinformatics
Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in the cerebrovascular system. ICAS causes a narrowing of the arterial lumen, thereby restricting blood flow, while aneurysms involve the ballooning of b...

Deep learning of noncontrast CT for fast prediction of hemorrhagic transformation of acute ischemic stroke: a multicenter study.

European radiology experimental
BACKGROUND: Hemorrhagic transformation (HT) is a complication of reperfusion therapy following acute ischemic stroke (AIS). We aimed to develop and validate a model for predicting HT and its subtypes with poor prognosis-parenchymal hemorrhage (PH), i...

Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study.

Frontiers in public health
OBJECTIVE: Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.

Deep Learning Radiomics Nomogram Based on MRI for Differentiating between Borderline Ovarian Tumors and Stage I Ovarian Cancer: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics nomogram (DLRN) based on T2-weighted MRI to distinguish between borderline ovarian tumors (BOTs) and stage I epithelial ovarian cancer (EOC) preoperatively.

Interpretable machine learning models for COPD ease of breathing estimation.

Medical & biological engineering & computing
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide and greatly reduces the quality of life. Utilizing remote monitoring has been shown to improve quality of life and reduce exacerbations, but remains an ongoing area of...