Deep learning in histopathology: the path to the clinic
Abstract Machine learning techniques have great potential to improve medical diagnostics,
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …
Spoof surface plasmon photonics
FJ Garcia-Vidal, AI Fernández-Domínguez… - Reviews of Modern …, 2022 - APS
In undergraduate courses on classical electromagnetism, it is taught that a perfect conductor
expels the electromagnetic (EM) field, and hence its surface is not able to support the …
expels the electromagnetic (EM) field, and hence its surface is not able to support the …
Organic Hybrid Perovskite (MAPbI3−xClx) for Thermochromic Smart Window with Strong Optical Regulation Ability, Low Transition Temperature, and Narrow …
Recently, organic hybrid halide perovskites have been found to show thermochromism with
good optical performance, which can be applied in smart windows to reduce building energy …
good optical performance, which can be applied in smart windows to reduce building energy …
Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images
Current diagnosis of glioma types requires combining both histological features and
molecular characteristics, which is an expensive and time-consuming procedure …
molecular characteristics, which is an expensive and time-consuming procedure …
Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self …
Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
Artificial intelligence-based pathology for gastrointestinal and hepatobiliary cancers
J Calderaro, JN Kather - Gut, 2021 - gut.bmj.com
Artificial intelligence (AI) can extract complex information from visual data. Histopathology
images of gastrointestinal (GI) and liver cancer contain a very high amount of information …
images of gastrointestinal (GI) and liver cancer contain a very high amount of information …
[HTML][HTML] Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology
J Shao, J Ma, Q Zhang, W Li, C Wang - Seminars in cancer biology, 2023 - Elsevier
Personalized treatment strategies for cancer frequently rely on the detection of genetic
alterations which are determined by molecular biology assays. Historically, these processes …
alterations which are determined by molecular biology assays. Historically, these processes …
[HTML][HTML] Vision transformer-based weakly supervised histopathological image analysis of primary brain tumors
Z Li, Y Cong, X Chen, J Qi, J Sun, T Yan, H Yang, J Liu… - IScience, 2023 - cell.com
Diagnosis of primary brain tumors relies heavily on histopathology. Although various
computational pathology methods have been developed for automated diagnosis of primary …
computational pathology methods have been developed for automated diagnosis of primary …
Hierarchical discriminative learning improves visual representations of biomedical microscopy
Learning high-quality, self-supervised, visual representations is essential to advance the
role of computer vision in biomedical microscopy and clinical medicine. Previous work has …
role of computer vision in biomedical microscopy and clinical medicine. Previous work has …
Colour adaptive generative networks for stain normalisation of histopathology images
Deep learning has shown its effectiveness in histopathology image analysis, such as
pathology detection and classification. However, stain colour variation in Hematoxylin and …
pathology detection and classification. However, stain colour variation in Hematoxylin and …