The surge in computer-based health surveillance applications, leveraging technologies like big data analytics, artificial intelligence, and the Internet of Things, aims to provide personalized and streamlined medical services. These applications enco...
Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of l...
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-de...
OBJECTIVES: To investigate the effectiveness of BMAX, a deep learning-based computer-aided detection system for detecting fibrosing interstitial lung disease (ILD) on chest radiographs among non-expert and expert physicians in the real-world clinical...
Classifying specimens is a critical component of ecological research, biodiversity monitoring and conservation. However, manual classification can be prohibitively time-consuming and expensive, limiting how much data a project can afford to process. ...
BACKGROUND: This study aimed to develop and validate radiomics and deep learning (DL) signatures for predicting distal metastasis (DM) of non-small cell lung cancer (NSCLC) in low-dose computed tomography (LDCT).
Advanced materials (Deerfield Beach, Fla.)
38168750
In the era of information, characterized by an exponential growth in data volume and an escalating level of data abstraction, there has been a substantial focus on brain-like chips, which are known for their robust processing power and energy-efficie...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
38160273
Classical machine learning and deep learning models for Computer-Aided Diagnosis (CAD) commonly focus on overall classification performance, treating misclassification errors (false negatives and false positives) equally during training. This uniform...
. The existing diagnostic paradigm for diabetic retinopathy (DR) greatly relies on subjective assessments by medical practitioners utilizing optical imaging, introducing susceptibility to individual interpretation. This work presents a novel system f...