His primary scientific interests are in Cancer research, Cancer, Pathology, Artificial intelligence and Breast cancer. The study incorporates disciplines such as Jurkat cells, DNA methylation, Transcription factor, Oncogene and Immunology in addition to Cancer research. His Cancer research is classified as research in Internal medicine.
His work carried out in the field of Pathology brings together such families of science as Neovascularization, Antigen, Lewis lung carcinoma, Cytotoxic T cell and In vivo. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning, Computer vision and Pattern recognition. His studies deal with areas such as Prostate and Histology as well as Prostate cancer.
His scientific interests lie mostly in Pathology, Cancer research, Cancer, Internal medicine and Breast cancer. His is doing research in Immunohistochemistry and Biopsy, both of which are found in Pathology. He works mostly in the field of Cancer research, limiting it down to topics relating to Immunology and, in certain cases, Cytotoxic T cell.
His study in Prostate cancer and Prostate is done as part of Cancer. His Prostate cancer research includes themes of Magnetic resonance imaging, Artificial intelligence and Histology. The Internal medicine study combines topics in areas such as Endocrinology and Oncology.
His primary areas of study are Internal medicine, Oncology, Breast cancer, Cancer research and Cancer. Michael Feldman has researched Oncology in several fields, including Stage, Biomarker, Progression-free survival and Proportional hazards model. His research investigates the link between Breast cancer and topics such as Disease that cross with problems in Primary tumor.
His studies in Cancer research integrate themes in fields like Immune checkpoint, Immune system, Immunology, Antigen and Germline. Michael Feldman works mostly in the field of Antigen, limiting it down to concerns involving T cell and, occasionally, Cytotoxic T cell. His study looks at the relationship between Cancer and fields such as Microbiome, as well as how they intersect with chemical problems.
The scientist’s investigation covers issues in Cancer research, Cancer, Internal medicine, Breast cancer and Artificial intelligence. His Cancer research study integrates concerns from other disciplines, such as Immune checkpoint, DNA methylation and Transcription factor, Gene, microRNA. His Cancer research incorporates themes from Microbiome, Non-coding RNA and Leukemia.
His Internal medicine study which covers Oncology that intersects with Progression-free survival, Immunotherapy and Ovarian cancer. The concepts of his Artificial intelligence study are interwoven with issues in Bioinformatics and Pattern recognition. His research in Pattern recognition intersects with topics in H&E stain and Digital pathology.
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Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer
Christina Twyman-Saint Victor;Andrew J. Rech;Amit Maity;Ramesh Rengan;Ramesh Rengan.
Nature (2015)
BRAF and RAS mutations in human lung cancer and melanoma
Marcia S. Brose;Patricia Volpe;Michael Feldman;Madhu Kumar.
Cancer Research (2002)
Hilbert transform in vibration analysis
Michael Feldman.
Mechanical Systems and Signal Processing (2011)
Tumor endothelium FasL establishes a selective immune barrier promoting tolerance in tumors.
Gregory T. Motz;Stephen P. Santoro;Li Ping Wang;Tom Garrabrant.
Nature Medicine (2014)
Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade.
Joseph L. Benci;Bihui Xu;Yu Qiu;Tony J. Wu.
Cell (2016)
Local recurrence in head and neck cancer: relationship to radiation resistance and signal transduction.
Anjali K Gupta;W Gillies McKenna;Charles N Weber;Michael D Feldman.
Clinical Cancer Research (2002)
Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks
Angel Cruz-Roa;Ajay Basavanhally;Fabio González;Hannah Leah Gilmore.
Proceedings of SPIE (2014)
Non-linear system vibration analysis using Hilbert transform--I. Free vibration analysis method 'Freevib'
Michael Feldman.
Mechanical Systems and Signal Processing (1994)
Digital imaging in pathology: whole-slide imaging and beyond.
Farzad Ghaznavi;Andrew Evans;Anant Madabhushi;Michael Feldman.
Annual Review of Pathology-mechanisms of Disease (2013)
Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology
S. Naik;S. Doyle;S. Agner;A. Madabhushi.
international symposium on biomedical imaging (2008)
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