A review of machine learning approaches, challenges and prospects for computational tumor pathology [PDF]
arXiv, 2022 Computational pathology is part of precision oncology medicine. The integration of high-throughput data including genomics, transcriptomics, proteomics, metabolomics, pathomics, and radiomics into clinical practice improves cancer treatment plans, treatment cycles, and cure rates, and helps doctors open up innovative approaches to patient prognosis. In
arxiv
Anatomy-Driven Pathology Detection on Chest X-rays [PDF]
arXiv, 2023 Pathology detection and delineation enables the automatic interpretation of medical scans such as chest X-rays while providing a high level of explainability to support radiologists in making informed decisions. However, annotating pathology bounding boxes is a time-consuming task such that large public datasets for this purpose are scarce.
arxiv
Quantitative and Qualitative Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis [PDF]
arXiv, 2020 Background: The lack of explanations for the decisions made by algorithms such as deep learning has hampered their acceptance by the clinical community despite highly accurate results on multiple problems. Recently, attribution methods have emerged for explaining deep learning models, and they have been tested on medical imaging problems.
arxiv
Soluble Epoxide Hydrolase Inhibition for Ocular Diseases: Vision for the Future [PDF]
, 2019 Ocular diseases cause visual impairment and blindness, imposing a devastating impact on quality of life and a substantial societal economic burden. Many such diseases lack universally effective pharmacotherapies.
Corson, Timothy W., Park, Bomina
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Imaging of Hepatocellular Carcinoma by Computed Tomography and Magnetic Resonance Imaging: State of the Art [PDF]
, 2009 Hepatocellular carcinoma (HCC) is a very frequent tumor worldwide. Its incidence is linked to the distribution of liver cirrhosis and viral hepatitis, which are the main risk factors for the development of HCC.
Herrmann, Karin A. +2 more
core +1 more source
안구내 약물 전달을 통한 시력을 위협하는 안질환 생쥐 모델의 질환 표현형 치료 연구 [PDF]
, 2023 학위논문(박사) -- 서울대학교대학원 : 의과대학 의과학과, 2023. 2. 김정훈.Introduction: Aberrant growth of blood vessels, neovascularization is a key feature of vision-threatening eye diseases, including retinopathy of prematurity, diabetic retinopathy, neovascular age-related ...
이석재
core
Blood Vessel Tortuosity Selects against Evolution of Agressive Tumor Cells in Confined Tissue Environments: a Modeling Approach [PDF]
PLoS Computational Biology 2017, 13(7): e1005635, 2017 Cancer is a disease of cellular regulation, often initiated by genetic mutation within cells, and leading to a heterogeneous cell population within tissues. In the competition for nutrients and growth space within the tumors the phenotype of each cell determines its success. Selection in this process is imposed by both the microenvironment (neighboring
arxiv +1 more source
Can the application of computed tomography laser mammography (CTLM) in dense breast (category 3,4 according to ACR) examinations combined with x-ray mammography enhance the detection of breast cancer? [PDF]
, 2009 Background: The aim of this study was an attempt to answer the question whether laser mammography in dense breast (classified as category 3,4 according to ACR) examination together with x-ray mammography can enhance the detection of breast cancer ...
Adamiak, Dagmara +6 more
core
Generative Adversarial Networks Synthesize Realistic OCT Images of the Retina [PDF]
arXiv, 2019 We report, to our knowledge, the first end-to-end application of Generative Adversarial Networks (GANs) towards the synthesis of Optical Coherence Tomography (OCT) images of the retina. Generative models have gained recent attention for the increasingly realistic images they can synthesize, given a sampling of a data type.
arxiv
Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning [PDF]
arXiv, 2023 The brain's biological age has been considered as a promising candidate for a neurologically significant biomarker. However, recent results based on longitudinal magnetic resonance imaging data have raised questions on its interpretation. A central question is whether an increased biological age of the brain is indicative of brain pathology and if ...
arxiv