[HTML][HTML] Artificial intelligence in pathology
HY Chang, CK Jung, JI Woo, S Lee… - … of pathology and …, 2019 - synapse.koreamed.org
As in other domains, artificial intelligence is becoming increasingly important in medicine. In
particular, deep learning-based pattern recognition methods can advance the field of …
particular, deep learning-based pattern recognition methods can advance the field of …
Imaging technologies for microfluidic biochips
With the growing interest in biochips, numerous efforts have been made to recapitulate a
more reliable and physiologically relevant environment within chips, resulting in significant …
more reliable and physiologically relevant environment within chips, resulting in significant …
Real-time diagnosis and visualization of tumor margins in excised breast specimens using fluorescence lifetime imaging and machine learning
Tumor-free surgical margins are critical in breast-conserving surgery. In up to 38% of the
cases, however, patients undergo a second surgery since malignant cells are found at the …
cases, however, patients undergo a second surgery since malignant cells are found at the …
An effective disease prediction system using incremental feature selection and temporal convolutional neural network
S Sandhiya, U Palani - Journal of Ambient Intelligence and Humanized …, 2020 - Springer
Rapid growth of communication technologies and expert systems produces enormous
volume of medical data. Deep learning technique is an advancement of machine learning …
volume of medical data. Deep learning technique is an advancement of machine learning …
Fully automated postlumpectomy breast margin assessment utilizing convolutional neural network based optical coherence tomography image classification method
Background The purpose of this study was to develop a deep learning classification
approach to distinguish cancerous from noncancerous regions within optical coherence …
approach to distinguish cancerous from noncancerous regions within optical coherence …
[HTML][HTML] The LMIT: Light-mediated minimally-invasive theranostics in oncology
Minimally-invasive diagnosis and therapy have gradually become the trend and research
hotspot of current medical applications. The integration of intraoperative diagnosis and …
hotspot of current medical applications. The integration of intraoperative diagnosis and …
[HTML][HTML] Binary dose level classification of tumour microvascular response to radiotherapy using artificial intelligence analysis of optical coherence tomography images
The dominant consequence of irradiating biological systems is cellular damage, yet
microvascular damage begins to assume an increasingly important role as the radiation …
microvascular damage begins to assume an increasingly important role as the radiation …
[PDF][PDF] 智能化精准光学诊疗技术研究进展
李阳曦， 胡成全， 马龙飞， 张欣然… - Chinese Journal of …, 2021 - researching.cn
摘要现代光学成像和光学治疗技术的发展, 为智能化精准微创诊疗平台的构建提供了重要的结构
支撑. 传统的诊断和治疗技术存在诊断与治疗过程相对独立, 术前, 术中信息不匹配 …
支撑. 传统的诊断和治疗技术存在诊断与治疗过程相对独立, 术前, 术中信息不匹配 …
Automated assessment of breast cancer margin in optical coherence tomography images via pretrained convolutional neural network
N Singla, K Dubey, V Srivastava - Journal of biophotonics, 2019 - Wiley Online Library
The benchmark method for the evaluation of breast cancers involves microscopic testing of a
hematoxylin and eosin (H&E)‐stained tissue biopsy. Resurgery is required in 20% to 30% of …
hematoxylin and eosin (H&E)‐stained tissue biopsy. Resurgery is required in 20% to 30% of …
[HTML][HTML] Rapid on-site AI-assisted grading for lung surgery based on optical coherence tomography
HC Liu, MH Lin, WC Chang, RC Zeng, YM Wang… - Cancers, 2023 - mdpi.com
Simple Summary In early-stage lung cancer surgery, determining the extent of resection
relies on microscopic examination of frozen sections (FSs), especially when the histology is …
relies on microscopic examination of frozen sections (FSs), especially when the histology is …