AIMC Topic: Male

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Plasma proteomics for biomarker discovery in childhood tuberculosis.

Nature communications
Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, thus a global priority is the identificati...

Automatic generation and risk stratification of carotid plaque in virtual shear wave elastography using a generative adversarial network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Shear wave elastography (SWE) is an effective ultrasound imaging technique for assessing carotid plaque vulnerability. However, acquiring SWE images typically requires costly specialized equipment and must be performed by experienced radiologists, wh...

Multi-modal predictive modeling of schizophrenia severity: Leveraging liver function indicators and cognitive scores with random forest and SVM.

Psychiatry research. Neuroimaging
Schizophrenia is a complex neuropsychiatric disorder with cognitive deficits and systemic physiological disturbances, including emerging links to hepatic dysfunction via the gut-liver-brain axis. Despite growing evidence, the integration of liver fun...

Visualized load-bearing-based robot control system improves early function in femoral neck fracture patients: a randomized controlled trial focusing on outcomes after total hip arthroplasty.

Journal of orthopaedic surgery and research
BACKGROUND: After total hip arthroplasty (THA), standing and walking balance are greatly affected in the early recovery period, making it important to increase weight-bearing amount (WBA) on the surgical side. Sometimes, traditional treatment methods...

Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: While the TNM staging system provides valuable insights into the extent of disease, predicting postoperative progression in early-stage non-small cell lung cancer (NSCLC) remains a significant challenge. An effective bioimaging prognostic...

AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.

Cardiovascular diabetology
BACKGROUND: Epicardial adipose tissue (EAT) is associated with cardiometabolic risk in type 2 diabetes (T2D), but its spatial distribution and structural alterations remain understudied. We aim to develop a shape-aware, AI-based method for automated ...

Open-access ultrasonic diaphragm dataset and an automatic diaphragm measurement using deep learning network.

Respiratory research
BACKGROUND: The assessment of diaphragm function is crucial for effective clinical management and the prevention of complications associated with diaphragmatic dysfunction. However, current measurement methodologies rely on manual techniques that are...

Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules.

BMC medical informatics and decision making
BACKGROUND: Pulmonary Nodules (PNs) are a trend considered as the early manifestation of lung cancer. Among them, PNs that remain stable for more than two years or whose pathological results suggest not being lung cancer are considered benign PNs (BP...

Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks.

BMC medical imaging
BACKGROUND: The skull is highly durable and plays a significant role in sex determination as one of the most dimorphic bones. The facial canal (FC), a clinically significant canal within the temporal bone, houses the facial nerve. This study aims to ...

Development of an artificial intelligence algorithm for automated surgical gestures annotation.

Journal of robotic surgery
Surgical gestures analysis is a promising method to assess surgical procedure quality, but manual annotation is time-consuming. We aimed to develop a recurrent neural network for automated surgical gesture annotation using simulated robot-assisted ra...