Junhao Wang

ORCID: 0000-0002-3938-8466
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About
Contact & Profiles
Research Areas
  • Image Enhancement Techniques
  • Face recognition and analysis
  • Advanced biosensing and bioanalysis techniques
  • Dengue and Mosquito Control Research
  • Gastrointestinal Tumor Research and Treatment
  • Face and Expression Recognition
  • Biomarkers in Disease Mechanisms
  • Mosquito-borne diseases and control
  • Ethics and Social Impacts of AI
  • Microfluidic and Bio-sensing Technologies
  • Radioactive element chemistry and processing
  • Artificial Intelligence in Healthcare and Education
  • Electrowetting and Microfluidic Technologies
  • Advanced Neural Network Applications
  • Genomics and Phylogenetic Studies
  • Identification and Quantification in Food
  • Hydrocarbon exploration and reservoir analysis
  • Remote-Sensing Image Classification
  • COVID-19 diagnosis using AI
  • Gastrointestinal Bleeding Diagnosis and Treatment
  • Gastrointestinal disorders and treatments
  • Geochemistry and Geologic Mapping
  • Nanoplatforms for cancer theranostics
  • AI in cancer detection
  • Nanoparticle-Based Drug Delivery

Shanghai Jiao Tong University
2024-2025

Chengdu University of Technology
2024

Hainan University
2023

Southeast University
2023

Southwest University
2023

Huazhong Agricultural University
2022

Shanghai University of Engineering Science
2021

In recent years, the deep integration of basic research and clinical translational nanotechnology oncology has led to emergence a new branch, namely integrated nano-oncology. This is an emerging important interdisciplinary field, which plays irreplaceable role in diagnosis, treatment, early warning, monitoring prevention tumors, become frontier. Here main advances nano-oncology was reviewed, mainly included controlled preparation nanomaterials, ultra-sensitive detection tumor biomarkers,...

10.26599/nbe.2024.9290060 article EN cc-by Nano Biomedicine and Engineering 2024-02-05

OPINION article Front. Public Health, 20 January 2023Sec. Planetary Health Volume 11 - 2023 | https://doi.org/10.3389/fpubh.2023.1115000

10.3389/fpubh.2023.1115000 article EN cc-by Frontiers in Public Health 2023-01-20

Facial keypoint detection technology faces significant challenges under conditions such as occlusion, extreme angles, and other demanding environments. Previous research has largely relied on deep learning regression methods using the face’s overall global template. However, these lack robustness in difficult conditions, leading to instability detecting facial keypoints. To address this challenge, we propose a joint optimization approach that combines with heatmaps, emphasizing importance of...

10.3390/app14167153 article EN cc-by Applied Sciences 2024-08-15

The term "own-race bias" (ORB) describes the situation in which people are more adept at identifying faces of members their own race than those other races. impact racial disparities on face recognition accuracy and speed is investigated this study. Empirical studies have demonstrated involvement variables including affect mental abilities ORB. While split attention tends to enhance ORB, positive emotions can decrease it. Positive emotional states may also boost cognitive flexibility, would...

10.54097/kxk18g29 article EN cc-by-nc Journal of Education Humanities and Social Sciences 2024-12-26

ABSTRACT Background Breast arterial calcification (BAC), visible on mammograms, has emerged as a biomarker of cardiovascular disease (CVD) in women. Barriers to clinical implementation BAC include limited studies with outcomes and lack quantification tools. Methods This single-center, retrospective study included women screening digital mammogram from 2008-2016. was quantified using an automated, artificial intelligence (AI)-generated Bradley score, binary (Bradley score ≥5) continuous...

10.1101/2023.09.29.23296371 preprint EN medRxiv (Cold Spring Harbor Laboratory) 2023-10-02
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