Hyo-Jung Lim

ORCID: 0000-0003-2615-1029
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Dysphagia Assessment and Management
  • Tracheal and airway disorders
  • AI in cancer detection
  • Muscle activation and electromyography studies
  • Conducting polymers and applications
  • Advanced Sensor and Energy Harvesting Materials
  • Obstructive Sleep Apnea Research
  • Esophageal and GI Pathology
  • Medical Image Segmentation Techniques
  • Voice and Speech Disorders
  • Ultrasound and Hyperthermia Applications
  • Ultrasound Imaging and Elastography
  • Non-Invasive Vital Sign Monitoring
  • Stroke Rehabilitation and Recovery
  • Radiomics and Machine Learning in Medical Imaging
  • Ergonomics and Musculoskeletal Disorders
  • Indoor and Outdoor Localization Technologies

Hong Kong Polytechnic University
2022-2023

Ultrasound elastography can quantify stiffness distribution of tissue lesions and complements conventional B-mode ultrasound for breast cancer screening. Recently, the development computer-aided diagnosis has improved reliability system, whilst inception machine learning, such as deep further extended its power by facilitating automated segmentation tumour classification. The objective this review was to summarize application learning model systems Review databases included PubMed, Web...

10.3390/cancers14020367 article EN Cancers 2022-01-12

Sleep posture has a crucial impact on the incidence and severity of obstructive sleep apnea (OSA). Therefore, surveillance recognition postures could facilitate assessment OSA. The existing contact-based systems might interfere with sleeping, while camera-based introduce privacy concerns. Radar-based overcome these challenges, especially when individuals are covered blankets. aim this research is to develop nonobstructive multiple ultra-wideband radar system based machine learning models. We...

10.3390/s23052475 article EN cc-by Sensors 2023-02-23

Elastography complements traditional medical imaging modalities by mapping tissue stiffness to identify tumors in the endocrine system, and machine learning models can further improve diagnostic accuracy reliability. Our objective this review was summarize applications performance of machine-learning-based elastography on classification tumors. Two authors independently searched electronic databases, including PubMed, Scopus, Web Science, IEEEXpress, CINAHL, EMBASE. Eleven (n = 11) articles...

10.3390/cancers15030837 article EN Cancers 2023-01-29

Dysphagia is one of the most common problems among older adults, which might lead to aspiration pneumonia and eventual death. It calls for a feasible, reliable, standardized screening or assessment method prompt rehabilitation measures mitigate risks dysphagia complications. Computer-aided using wearable technology could be solution problem but not clinically applicable because heterogeneity protocols. The aim this paper formulate unify swallowing protocol, named Comprehensive Assessment...

10.3390/ijerph20042998 article EN International Journal of Environmental Research and Public Health 2023-02-08

Emerging sleep health technologies will have an impact on monitoring patients with disorders. This study proposes a new deep learning model architecture that improves the under-blanket posture classification accuracy by leveraging anatomical landmark feature through attention strategy. The system used integrated visible light and depth camera. Deep models (ResNet-34, EfficientNet B4, ECA-Net50) were trained using images. We compared without coordinate input generated open-source pose...

10.3390/ijerph192013491 article EN International Journal of Environmental Research and Public Health 2022-10-18
Coming Soon ...