Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...
American Institute of Physics

Using deep learning to better forecast tropical cyclone tracks and intensities

Integrating deep learning with traditional forecasting techniques can improve early warning systems by capitalizing on each ...
Justdial on MSN

Machine learning vs deep learning: Which one is better?

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in ...
2 Minute Medicine

Deep-learning models displayed expert-level accuracy in detecting epileptiform discharges on electroencephalogram (EEG) recordings

Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...
GEN - Genetic Engineering and Biotechnology News

Deep Learning Model Developed to Help Predict Functional Impact of Regulatory Mutations

Researchers say the deep learning model may help to create leads for new cancer diagnostics, patient stratification, and future therapies.
ascopubs.org

Deep-Learning Model for Real-Time Prediction of Recurrence in Early-Stage Non–Small Cell Lung Cancer: A Multimodal Approach (RADAR CARE Study)

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
TMCnet

Food Allergy Diagnostics are Enhanced by Machine Learning and Deep Learning AI Models

The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...
Ophthalmology Advisor

Retinal Detachment Diagnosis Strong Using Deep Learning-Powered Fundus Images

Retinal detachments can be diagnosed using a deep learning-powered fundus imaging system, offering expertise to screening sites.