AIMC Topic: Humans

Clear Filters Showing 24301 to 24310 of 95995 articles

Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms.

Journal of imaging informatics in medicine
Breast cancer is the most common cancer in women. Ultrasound is one of the most used techniques for diagnosis, but an expert in the field is necessary to interpret the test. Computer-aided diagnosis (CAD) systems aim to help physicians during this pr...

Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy.

Physical and engineering sciences in medicine
Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can result in severe complications. The proposed eye positioning and tracking system (EPTS) was designed to...

Multi-file dynamic compression method based on classification algorithm in DNA storage.

Medical & biological engineering & computing
The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its develo...

Optimization of mid-infrared noninvasive blood-glucose prediction model by support vector regression coupled with different spectral features.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Mid-infrared spectral analysis of glucose in subcutaneous interstitial fluid has been widely employed as a noninvasive alternative to the standard blood-glucose detection requiring blood-sampling via skin-puncturing, but improving the confidence leve...

Development of high-quality artificial intelligence for computer-aided diagnosis in determining subtypes of colorectal cancer.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: There are no previous studies in which computer-aided diagnosis (CAD) diagnosed colorectal cancer (CRC) subtypes correctly. In this study, we developed an original CAD for the diagnosis of CRC subtypes.

Identification of chronic non-atrophic gastritis and intestinal metaplasia stages in the Correa's cascade through machine learning analyses of SERS spectral signature of non-invasively-collected human gastric fluid samples.

Biosensors & bioelectronics
The progression of gastric cancer involves a complex multi-stage process, with gastroscopy and biopsy being the standard procedures for diagnosing gastric diseases. This study introduces an innovative non-invasive approach to differentiate gastric di...

Predicting lower limb lymphedema after cervical cancer surgery using artificial neural network and decision tree models.

European journal of oncology nursing : the official journal of European Oncology Nursing Society
PURPOSE: This study aimed to develop and validate accessible artificial neural network and decision tree models to predict the risk of lower limb lymphedema after cervical cancer surgery.

A novel two-layer fuzzy neural network for solving inequality-constrained ℓ-minimization problem with applications.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a novel two-layer fuzzy neural network model (TLFNN) for solving the inequality-constrained ℓ-minimization problem. The stability and global convergence of the proposed TLFNN model are detailedly analyzed using the Lyapunov ...

Aligning the domains in cross domain model inversion attack.

Neural networks : the official journal of the International Neural Network Society
Model Inversion Attack reconstructs confidential training dataset from a target deep learning model. Most of the existing methods assume the adversary has an auxiliary dataset that has similar distribution with the private dataset. However, this assu...

Dual-stream multi-dependency graph neural network enables precise cancer survival analysis.

Medical image analysis
Histopathology image-based survival prediction aims to provide a precise assessment of cancer prognosis and can inform personalized treatment decision-making in order to improve patient outcomes. However, existing methods cannot automatically model t...