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AI in Cancer Detection

AI in Cancer Detection

72 faculty research AI in Cancer Detection on GradNova.

J
Artificial Intelligence: AI Interpretability, Classification and Clustering, Unsupervised/supervised Learning, Real-Time Object Detection
Electricity Market: Ev Charging, Transmission Planning, Energy Storage Optimization, Distributed Energy Resources Management
Operations Management: Inventory and Pricing, Behavioral Queueing, Game Theory, Uncertain Decision Making, Supply Chain Optimization, Complex Product Research and Development
Gene Expression and Cancer Classification
+4
M
AI in Cancer Detection
Generative Adversarial Networks and Image Synthesis
Multimodal Machine Learning Applications
D
Dong Hye Ye

Computer Science Assistant Professor

Computer Science

Georgia State University

Advanced X-Ray and Ct Imaging
AI in Cancer Detection
Functional Brain Connectivity Studies
Medical Image Segmentation Techniques
+1
N
Field-Programmable Gate Arrays
Quantum Computing
Reconfigurable Computing
Brain Tumor Detection and Classification
+3
J
Advanced Neural Network Applications
AI in Cancer Detection
Domain Adaptation and Few-Shot Learning
Medical Image Segmentation Techniques
+1
C
Advanced Neural Network Applications
Advanced Neuroimaging Techniques and Applications
AI in Cancer Detection
Domain Adaptation and Few-Shot Learning
+1
K
AI in Cancer Detection
COVID-19 Diagnosis Using AI
Generative Adversarial Networks and Image Synthesis
Machine Learning in Healthcare
+1
M
AI in Cancer Detection
Medical Image Segmentation Techniques
Nuclear Materials and Properties
Nuclear Reactor Physics and Engineering
+1
B
Biomedical Engineering
Machine Learning
Neuroscience
Advanced Neural Network Applications
+2
Z
Zeyun Yu

Professor, Computer Science; Professor, Biomedical Engineering; Director, Big Data Analytics and Visualization Lab

Computer Science

University of Wisconsin–Milwaukee

3D Shape Modeling and Analysis
AI in Cancer Detection
Computer Graphics and Visualization Techniques
Image Retrieval and Classification Techniques
+1
L
Linda G. Shapiro

Professor; Boeing Professor in Computer Science & Engineering

Department of Electrical and Computer Engineering

University of Washington

Biosystems
Computer Vision
Data Mining
Machine Learning
+7
S
Artificial Intelligence (image Analysis and Computer Vision)
Visual Computing (image Analysis)
Medical Image Segmentation Techniques
Medical Imaging and Analysis
+3
A
AI in Healthcare
Deep Learning
Interpretable Machine Learning
AI in Cancer Detection
+4
S
Computer Graphics
Human and Computer Vision
Image Display and Analysis
Medical Imaging
+5
A
AI in Cancer Detection
Generative Adversarial Networks and Image Synthesis
Solar and Space Plasma Dynamics
Sparse and Compressive Sensing Techniques
+1
M
AI in Cancer Detection
Anomaly Detection Techniques and Applications
COVID-19 Diagnosis Using AI
Maritime Navigation and Safety
+1
H
Computer Vision
Machine Learning
Generative Adversarial Networks and Image Synthesis
AI in Cancer Detection
+3
X
Machine Learning
Natural Language Processing
Public Health
Medical Image Segmentation Techniques
+4
N
Cloud Computing
Computer Communications and Networks
Dependable Computing and Networked Systems.
High-Performance Computer Architecture and Systems
+3
M
AI for Healthcare
Data Mining
Graph Learning
Machine Learning
+3
A
Abdullah-Al-Zubaer Imran

Assistant Professor, Lighthouse Beacon Foundation Faculty Scholar

Computer Science

University of Kentucky

Advanced X-Ray and Ct Imaging
AI in Cancer Detection
Medical Imaging Techniques and Applications
Radiation Dose and Imaging
+1
V
V. K. Cody Bumgardner, PhD

Associate Professor of Pathology and Laboratory Medicine; Assistant Dean for Artificial Intelligence and Data Science, College of Medicine; Division Chief, Pathology Informatics; Director, IBI Center for Applied AI

Computer Science

University of Kentucky

AI in Cancer Detection
Cell Image Analysis Techniques
Digital Imaging for Blood Diseases
D
AI in Cancer Detection
Distributed Control Multi-Agent Systems
DNA and Biological Computing
Medical Image Segmentation Techniques
+1
P
Applications of Machine Learning to Physics
Astronomy
Climate
Learning in Biological Systems
+8
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