What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Internal medicine
- Radiology
Artificial intelligence, Cardiology, Internal medicine, Radiology and Wireless sensor network are his primary areas of study.
Heye Zhang combines subjects such as Machine learning, Computer vision and Pattern recognition with his study of Artificial intelligence.
His Computer vision research includes themes of Kalman filter, Carotid arteries and Ultrasound.
His work in the fields of Myocardial infarction overlaps with other areas such as Photoplethysmogram, Pulse rate variability and Coherence spectrum.
His Radiology research is multidisciplinary, incorporating perspectives in Common carotid artery, Retrospective cohort study, Transfer function and Nonlinear system.
His work deals with themes such as Key generation, Encryption and Data transmission, which intersect with Wireless sensor network.
His most cited work include:
- Unobtrusive Sensing and Wearable Devices for Health Informatics (464 citations)
- A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network. (112 citations)
- OpenCMISS:A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project (92 citations)
What are the main themes of his work throughout his whole career to date?
Heye Zhang focuses on Artificial intelligence, Internal medicine, Cardiology, Pattern recognition and Computer vision.
His studies in Deep learning, Segmentation, Artificial neural network, Feature extraction and Feature are all subfields of Artificial intelligence research.
His Internal medicine research focuses on Common carotid artery in particular.
As part of his studies on Cardiology, Heye Zhang often connects relevant areas like Blood pressure.
His Pattern recognition research incorporates themes from Modality and Robustness.
In Computer vision, Heye Zhang works on issues like Kalman filter, which are connected to Nonlinear system, Algorithm, Filter and Ultrasound.
He most often published in these fields:
- Artificial intelligence (38.07%)
- Internal medicine (18.27%)
- Cardiology (17.77%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (38.07%)
- Pattern recognition (15.23%)
- Segmentation (13.20%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Pattern recognition, Segmentation, Deep learning and Feature.
The Artificial intelligence study combines topics in areas such as Machine learning and Computer vision.
The study incorporates disciplines such as Representation and Ultrasound in addition to Computer vision.
His Discriminative model study in the realm of Pattern recognition connects with subjects such as Regression.
His research in Segmentation intersects with topics in Image quality, Anatomy and Atrial fibrillation, Left atrium.
In his research, Myocardial infarction and Algorithm is intimately related to Magnetic resonance imaging, which falls under the overarching field of Image segmentation.
Between 2017 and 2021, his most popular works were:
- Heartbeats Based Biometric Random Binary Sequences Generation to Secure Wireless Body Sensor Networks (87 citations)
- Motion Tracking of the Carotid Artery Wall From Ultrasound Image Sequences: a Nonlinear State-Space Approach (82 citations)
- Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI (63 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Internal medicine
- Radiology
Heye Zhang spends much of his time researching Artificial intelligence, Feature extraction, Computer vision, Deep learning and Segmentation.
His Artificial intelligence research includes elements of Machine learning and Pattern recognition.
His Pattern recognition research includes themes of Heartbeat, Feature, Biometrics, Wireless sensor network and Electrocardiography.
His study in Feature extraction is interdisciplinary in nature, drawing from both Active learning, Cardiac arrhythmia, Pixel, Support vector machine and Feature learning.
The Computer vision study combines topics in areas such as Representation and Ultrasound.
In his work, Left atrial, Left atrium, Atrial fibrillation, Scar tissue and Scars is strongly intertwined with Anatomy, which is a subfield of Segmentation.
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