AIMC Topic: Deep Learning

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Deep-learning method for data association in particle tracking.

Bioinformatics (Oxford, England)
MOTIVATION: Biological studies of dynamic processes in living cells often require accurate particle tracking as a first step toward quantitative analysis. Although many particle tracking methods have been developed for this purpose, they are typicall...

Feasibility of using deep learning to detect coronary artery disease based on facial photo.

European heart journal
AIMS: Facial features were associated with increased risk of coronary artery disease (CAD). We developed and validated a deep learning algorithm for detecting CAD based on facial photos.

Inverse mechano-electrical reconstruction of cardiac excitation wave patterns from mechanical deformation using deep learning.

Chaos (Woodbury, N.Y.)
The inverse mechano-electrical problem in cardiac electrophysiology is the attempt to reconstruct electrical excitation or action potential wave patterns from the heart's mechanical deformation that occurs in response to electrical excitation. Becaus...

Potential of Artificial Intelligence for Estimating Japanese Fetal Weights.

Acta medica Okayama
We developed an artificial intelligence (AI) method for estimating fetal weights of Japanese fetuses based on the gestational weeks and the bi-parietal diameter, abdominal circumference, and femur length. The AI comprised of neural network architectu...

Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs).

Journal of drugs in dermatology : JDD
BACKGROUND: Drug resistance to biologics in psoriasis therapy can occur – it may be acquired during a treatment or else present itself from the beginning. To date, no biomarkers are known that may reliably guide clinicians in predicting respons...

A comprehensive review of deep learning applications in hydrology and water resources.

Water science and technology : a journal of the International Association on Water Pollution Research
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water...

Incorporating higher order thinking and deep learning in a large, lecture-based human physiology course: can we do it?

Advances in physiology education
Large classes taught with didactic lectures and assessed with multiple-choice tests are commonly reported to promote lower order (LO) thinking and a surface approach (SA) to learning. Using a case study design, we hypothesized that incorporating inst...