The application of artificial intelligence in glaucoma diagnosis and prediction
L Zhang, L Tang, M **a, G Cao - Frontiers in cell and developmental …, 2023 - frontiersin.org
Artificial intelligence is a multidisciplinary and collaborative science, the ability of deep
learning for image feature extraction and processing gives it a unique advantage in dealing …
learning for image feature extraction and processing gives it a unique advantage in dealing …
Inflation of test accuracy due to data leakage in deep learning-based classification of OCT images
In the application of deep learning on optical coherence tomography (OCT) data, it is
common to train classification networks using 2D images originating from volumetric data …
common to train classification networks using 2D images originating from volumetric data …
Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine
Personalized medicine transforms healthcare by adapting interventions to individuals'
unique genetic, molecular, and clinical profiles. To maximize diagnostic and/or therapeutic …
unique genetic, molecular, and clinical profiles. To maximize diagnostic and/or therapeutic …
High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition
Sperm cell motility and morphology observed under the bright field microscopy are the only
criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) …
criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) …
Differentiation of breast tissue types for surgical margin assessment using machine learning and polarization-sensitive optical coherence tomography
We report an automated differentiation model for classifying malignant tumor, fibro-adipose,
and stroma in human breast tissues based on polarization-sensitive optical coherence …
and stroma in human breast tissues based on polarization-sensitive optical coherence …
[HTML][HTML] Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease of Diospyros kaki Leaves Using …
Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading
to substantial harvest reductions. Existing visual and destructive inspection methods suffer …
to substantial harvest reductions. Existing visual and destructive inspection methods suffer …
CDC-Net: Cascaded decoupled convolutional network for lesion-assisted detection and grading of retinopathy using optical coherence tomography (OCT) scans
Retinopathy refers to any injury in the retinal region of the eye that can lead to distorted
vision or even blindness. The segmentation of retinal lesions or biomarkers is crucial for the …
vision or even blindness. The segmentation of retinal lesions or biomarkers is crucial for the …
[BUCH][B] Interpretability in deep learning
This book is motivated by the large gap between the black-box nature of deep learning
architectures and the human interpretability of the knowledge models they encode. It is …
architectures and the human interpretability of the knowledge models they encode. It is …
Point‐of‐care devices based on fluorescence imaging and spectroscopy for tumor margin detection during breast cancer surgery: Towards breast conservation …
Objective Fluorescence‐based methods are highly specific and sensitive and have potential
in breast cancer detection. Simultaneous fluorescence imaging and spectroscopy during …
in breast cancer detection. Simultaneous fluorescence imaging and spectroscopy during …
Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network
Identification of the seed varieties is essential in the quality control and high yield crop
growth. The existing methods of varietal identification rely primarily on visual examination …
growth. The existing methods of varietal identification rely primarily on visual examination …