AI/ML for Smart Health
Figure 1, AI Doctor &
Digital Assistant by capitalizing on a mixture of AI medical
systems for providing the best care for anyone, anywhere,
and anytime
1. AI Medical System for Breast
Cancer Detection: "Innovative AI Model for Accurately
Predicting Margin Positivity from Intraoperative Digital Specimen
Mammograms to Guide Surgical Decision-making and Reduce
Re-excision Rates" (
system
architecture)
project lead: prof. Liu
members: C. Yang, S. Chen, R.R.
Yesgari, K.S. Ganni, J.B.R. Kallam, C. Sharma, D. Jeet
2. Privacy-preserving and
Interpretable AI Rosacea Detection using Deep Learning:
"Innovative AI for Rosacea Detection and Innovating
Interpretability of AI Models for Enhancing Trust and
Adoptability" (
system
architecture)
project lead: prof. Liu
members: C. Yang, P. Pechetti, K.
Kanda, R.R. Yesgari
award: NJIT Grace Hopper Artificial
Intelligence Research Institute seed grant, NJIT, 2025-2026.
3. AI Medical System for
Parkinson's Disease Detection: "Robust Parkinson's
Disease Early Detection Using Advanced Open and Scalable AI with
the Optimal Feature Extraction and the Bayes Classifier" (
system
architecture)
project lead: prof. Liu
members: Z. Yu, C. Sharma, J.A.
Mehta, N.N. Kantaria, C. Qiao
4. AI Medical System for
Alzheimer's Disease Detection: "Deep Learning Based
Prediction of Alzheimer's Disease Conversion From Mild Cognitive
Impairment Using Structural MRI: Toward an Early-Detection AI
Doctor" (
system
architecture)
project lead: prof. Liu
members: C. Yang, R.R. Yesgari, K.
Kanda, J.A. Mehta, J.B.R. Kallam, S. Chen
CBS
Evening News (November 7, 2025)
5. AI Medical System for
Automatic Brain Tumor Detection: "ASHVINI: AI Surgical
Histopathology Visualization & Interpretable Network
Intelligence for Glioma Detection" (
system
architecture)
project lead: prof. Liu, Dr. Hadi
members: C. Sharma, K.S. Ganni
6. AI Medical System for Medical
Data Security: "Innovative Artificial Intelligence
Framework for Medical Data Security in Large Language Models" (
system
architecture)
project lead: prof. Liu, Dr. Hadi
members: Z. Yu, C. Sharma, N.N.
Kantaria, A. Sharma
7. AI Medical System for
Electronic Health Records Prediction: "LLM–LNN
Neuro-Symbolic Framework for Explainable Healthcare Cost
Prediction from Electronic Health Records" (
system
architecture)
project lead: prof. Liu, Dr. Hadi
members: C. Yang, Z. Yu, S. Chen,
R.R. Yesgari, K.S. Ganni, K. Kanda, D. Jeet
Papers:
- C. Yang and C. Liu, "Towards Building AI
Doctor and Digital Assistant by Capitalizing on A Mixture of
AI Medical Systems", the 6th International Conference on
Medical Imaging and Computer-Aided Diagnosis, Nov.
19-21, 2025, London, UK
- C. Yang, R. Yesgari, and C. Liu,
"Privacy-Preserving Automated Rosacea Detection Based on
Medically Inspired Region of Interest Selection", IEEE
International Conference on Electrical and Computer
Engineering Researches, 06-08 December 2025,
Antananarivo, MADAGASCAR
- C. Yang and C. Liu, "Investigating the Impact
of Various Loss Functions and Learnable Wiener Filter for
Laparoscopic Image Desmoking", the 6th International
Conference on Medical Imaging and Computer-Aided Diagnosis,
Nov. 19-21, 2025, London, UK
- C. Yang, R. Yesgari, and C. Liu, "Patch-based
Automatic Rosacea Detection Using the ResNet Deep Learning
Framework", the 6th International Conference on Medical
Imaging and Computer-Aided Diagnosis, Nov. 19-21, 2025,
London, UK
- C. Yang and C. Liu, "Laparoscopic Image
Desmoking Using the U-Net with New Loss Function and
Integrated Differentiable Wiener Filter", IEEE the 11th
International Conference on Big Data Computing Service and
Machine Learning Applications, July 21-24, 2025,
Tucson, Arizona
- C. Yang and C. Liu, "Interpretable Automatic
Rosacea Detection with Whitened Cosine Similarity", IEEE
the 17th International Conference on Computer Research and
Development, January 17-19, 2025, Jiangxi, China
- C. Yang and C. Liu, "Increasing Rosacea
Awareness Among Population Using Deep Learning and
Statistical Approaches", The 5th International
Conference on Medical Imaging and Computer-Aided Diagnosis,
Nov. 19-21, 2024, Manchester, UK
- here
for more papers
