Two-photon high-speed fluorescence calcium imaging stands as a mainstream technique in neuroscience for capturing neural activities with high spatiotemporal resolution. However, challenges arise from the inherent tradeoff between acquisition speed an...
Globally, cardiovascular diseases (CVDs) are a leading cause of death; however, their impact can be greatly mitigated by early detection and treatment. Machine learning (ML)-based algorithms that use features extracted from electrocardiogram (ECG) si...
BACKGROUND: Cell type prediction is crucial to cell type identification of genomics, cancer diagnosis and drug development, and it can solve the time-consuming and difficult problem of cell classification in biological experiments. Therefore, a compu...
The main bottleneck in training a robust tumor segmentation algorithm for non-small cell lung cancer (NSCLC) on H&E is generating sufficient ground truth annotations. Various approaches for generating tumor labels to train a tumor segmentation model ...
OBJECTIVE: Colorectal cancer (CRC) is the fourth most common cancer in the UK. Patients with symptoms suggestive of CRC should be referred for urgent investigation. However, gastrointestinal symptoms are often non-specific and there is a need for sui...
The current detection method for Chikungunya Virus (CHIKV) involves an invasive and costly molecular biology procedure as the gold standard diagnostic method. Consequently, the search for a non-invasive, more cost-effective, reagent-free, and sustain...
Artificial intelligence (AI) has already found its way into ophthalmology, with the first approved algorithms that can be used in clinical routine. Retinal diseases in particular are proving to be an important area of application for AI, as they are ...
Journal of medical engineering & technology
Sep 16, 2024
An early detection of lung tumors is critical for better treatment results, and CT scans can reveal lumps in the lungs which are too small to be picked up by conventional X-rays. CT imaging has advantages, but it also exposes a person to radiation fr...
OBJECTIVE: To develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.
Revista da Associacao Medica Brasileira (1992)
Sep 16, 2024
OBJECTIVE: The study used machine learning models to predict the clinical outcome with various attributes or when the models chose features based on their algorithms.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.