Member of the Association of American Physicians
His scientific interests lie mostly in Radiology, Internal medicine, Clinical trial, Oncology and Surgery. The study incorporates disciplines such as Image processing and Nuclear medicine in addition to Radiology. His studies in Clinical trial integrate themes in fields like Positron emission tomography, Medical physics and Lymphoma.
His biological study spans a wide range of topics, including Solid tumor and Pathology. His Oncology research integrates issues from Carcinoma, Neoplasm staging and Proportional hazards model. His study in the fields of Clinical endpoint, Survival rate and Asymptomatic under the domain of Surgery overlaps with other disciplines such as Key issues.
His primary areas of study are Radiology, Internal medicine, Oncology, Clinical trial and Nuclear medicine. His research in Radiology intersects with topics in Colorectal cancer and Metastasis. His study in Internal medicine is interdisciplinary in nature, drawing from both Gastroenterology and Surgery.
His Oncology study combines topics from a wide range of disciplines, such as Clinical endpoint, Carcinoma, Hazard ratio, Nivolumab and Prostate cancer. His biological study spans a wide range of topics, including Positron emission tomography and Medical physics. His Nuclear medicine research is multidisciplinary, incorporating perspectives in Segmentation and Lung cancer.
Lawrence H. Schwartz mostly deals with Internal medicine, Oncology, Lung cancer, In patient and Lung. His work investigates the relationship between Internal medicine and topics such as Gastroenterology that intersect with problems in Spleen, Carbohydrate metabolism and Fdg pet ct. He interconnects Clinical endpoint, Clinical trial, Sorafenib, Immune checkpoint inhibitors and Docetaxel in the investigation of issues within Oncology.
His Lung cancer study integrates concerns from other disciplines, such as Receiver operating characteristic, Carcinoma, Radiomics, Artificial intelligence and Pattern recognition. His Carcinoma research is under the purview of Pathology. The study incorporates disciplines such as Medical physics, Disease, Generalizability theory and Treatment response in addition to Cancer.
Lawrence H. Schwartz mainly investigates Internal medicine, Oncology, Cancer, Artificial intelligence and Retrospective cohort study. His Internal medicine research incorporates elements of Gastroenterology and Melanoma. His Oncology research includes elements of Clinical trial, Chemotherapy, Hazard ratio, Confidence interval and Proportional hazards model.
His Clinical trial study incorporates themes from Magnetic resonance imaging and Image acquisition. His studies deal with areas such as Applications of artificial intelligence, Generalizability theory and Medical imaging as well as Cancer. The various areas that Lawrence H. Schwartz examines in his Artificial intelligence study include Disease and Pattern recognition.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
Elizabeth Eisenhauer;Patrick Therasse;Jan Bogaerts;L.H. Schwartz.
European Journal of Cancer (2009)
Recommendations for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The Lugano Classification
Bruce D. Cheson;Richard I. Fisher;Sally F. Barrington;Franco Cavalli.
Journal of Clinical Oncology (2014)
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer.
IEEE Transactions on Medical Imaging (2015)
Use of Positron Emission Tomography for Response Assessment of Lymphoma: Consensus of the Imaging Subcommittee of International Harmonization Project in Lymphoma
Malik E. Juweid;Sigrid Stroobants;Otto S. Hoekstra;Felix M. Mottaghy.
Journal of Clinical Oncology (2007)
The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.
Samuel G. Armato;Geoffrey McLennan;Luc Bidaut;Michael F. McNitt‐Gray.
Medical Physics (2011)
Role of Imaging in the Staging and Response Assessment of Lymphoma: Consensus of the International Conference on Malignant Lymphomas Imaging Working Group
Sally F. Barrington;N. George Mikhaeel;Lale Kostakoglu;Michel Meignan.
Journal of Clinical Oncology (2014)
Prognostic Factors for Survival in Previously Treated Patients With Metastatic Renal Cell Carcinoma
Robert J. Motzer;Jennifer Bacik;Lawrence H. Schwartz;Victor Reuter.
Journal of Clinical Oncology (2004)
Deep inspiration breath-hold technique for lung tumors: the potential value of target immobilization and reduced lung density in dose escalation ☆
Joseph Hanley;Marc M. Debois;Dennis Mah;Gikas S. Mageras.
International Journal of Radiation Oncology Biology Physics (1996)
Artificial intelligence in radiology
Ahmed Hosny;Chintan Parmar;John Quackenbush;Lawrence H. Schwartz;Lawrence H. Schwartz.
Nature Reviews Cancer (2018)
Trial Design and Objectives for Castration-Resistant Prostate Cancer: Updated Recommendations From the Prostate Cancer Clinical Trials Working Group 3
Howard I. Scher;Michael J. Morris;Walter M. Stadler;Celestia Higano.
Journal of Clinical Oncology (2016)
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