Not logged in Share Save
Share Save
Share Save
Share Save
DICER1 mutations in Bethesda III/IV thyroid cytology samples: A multicenter observational study Karimkhan, Afreen; Xia, Rong; Diaz, DeAnna; Wald, Abigail; Hodak, Steven; Givi, Babak; Khader, Samer; Pantanowitz, Liron; Liu, Xiaoying; Brandler, Tamar C. Share Save
Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches Kamble, Tejasvi Sanjay; Wang, Hongtao; Myers, Nicole; Littlefield, Nickolas; Reid, Leah; Mccarthy, Cynthia S.; Lee, Young Ji; Liu, Hongfang; Pantanowitz, Liron; Amirian, Soheyla; Rashidi, Hooman H.; Tafti, Ahmad P. Share Save
Introduction to Artificial Intelligence and Machine Learning in Pathology and Medicine: Generative and Nongenerative Artificial Intelligence Basics Rashidi, Hooman H.; Pantanowitz, Joshua; Hanna, Matthew G.; Tafti, Ahmad P.; Sanghani, Parth; Buchinsky, Adam; Fennell, Brandon; Deebajah, Mustafa; Wheeler, Sarah; Pearce, Thomas; Abukhiran, Ibrahim; Robertson, Scott; Palmer, Octavia; Gur, Mert; Tran, Nam K.; Pantanowitz, Liron Share Save
Generative Artificial Intelligence in Pathology and Medicine: A Deeper Dive Rashidi, Hooman H.; Pantanowitz, Joshua; Chamanzar, Alireza; Fennell, Brandon; Wang, Yanshan; Gullapalli, Rama R.; Tafti, Ahmad; Deebajah, Mustafa; Albahra, Samer; Glassy, Eric; Hanna, Matthew G.; Pantanowitz, Liron Share Save
Share Save
Share Save
Nongenerative Artificial Intelligence in Medicine: Advancements and Applications in Supervised and Unsupervised Machine Learning Pantanowitz, Liron; Pearce, Thomas; Abukhiran, Ibrahim; Hanna, Matthew; Wheeler, Sarah; Soong, T. Rinda; Tafti, Ahmad P.; Pantanowitz, Joshua; Lu, Ming Y.; Mahmood, Faisal; Gu, Qiangqiang; Rashidi, Hooman H. Share Save
Share Save
Statistics of Generative Artificial Intelligence and Nongenerative Predictive Analytics Machine Learning in Medicine Rashidi, Hooman H.; Hu, Bo; Pantanowitz, Joshua; Tran, Nam; Liu, Silvia; Chamanzar, Alireza; Gur, Mert; Chang, Chung-Chou H.; Wang, Yanshan; Tafti, Ahmad; Pantanowitz, Liron; Hanna, Matthew G. Share Save
KRAS Wild-Type Intraductal Papillary Mucinous Neoplasms (IPMNs) are Characterized by Recurrent Alterations in BRAF, ALK, and NTRK3 Wald, Abigail; Smith, Katelyn; Lajara, Sigfred; Ohori, N. Paul; Shaker, Nuha; Pantanowitz, Liron; Nikiforova, Marina; Singhi, Aatur Share Save
Comparison of Tumor-Infiltrating Lymphocyte Quantification Using AI-Based H&E Analysis Versus CD8 Immunohistochemistry Across Multiple Tumor Types Bedell, Mariel; Neyaz, Azfar; Pantanowitz, Liron; Hanna, Matthew; Pearce, Thomas; Rashidi, Hooman; Seigh, Lindsey; Surakji, Hamdi; Christensen, Daniel; Baki, M-Nasan Abdul; Baroudi, Ihsan; Khader, Samer; Abukhiran, Ibrahim Share Save
Predicting Histologic Grade, T-Stage, and Risk Stratification Group of Gastrointestinal Stromal Tumors (GISTs) Using Digitally Quantified Tumor Cellular Density (TCD) from Limited Tissue Samples Christensen, Daniel; Bedell, Mariel; Neyaz, Azfar; Rammal, Rayan; Baki, M-Nasan Abdul; Noor, Zobash; Baroudi, Ihsan; Surakji, Hamdi; Pantanowitz, Liron; Rashidi, Hooman; Hanna, Matthew; Pearce, Thomas; Seigh, Lindsey; Khader, Samer; Mansour, Akila; Abukhiran, Ibrahim Share Save
Share Save
Impact of Antibody Clone and Chromogen Changes on the Quantification of CD8-Positive Tumor-Infiltrating Lymphocytes in Melanoma: A Quantitative Imaging Analysis Study Surakji, Hamdi; Abukhiran, Ibrahim; Pantanowitz, Liron; Rashidi, Hooman; Pearce, Thomas; Seigh, Lindsey; Baki, M. Nasan Abdul; Christensen, Daniel; Hanna, Matthew; Baroudi, Ihsan; Deebajah, Mustafa; Khader, Samer Share Save
DNA/RNA-Based Next-Generation Sequencing (NGS) Improves the Early Diagnosis and Management of Malignant Bile Duct Strictures: A Five-Year, Prospective, Multi-Institutional Study Shaker, Nuha; Wald, Abigail; Smith, Katelyn; Lajara, Sigfred; Ohori, N. Paul; Pantanowitz, Liron; Nikiforova, Marina; Singhi, Aatur Share Save
.png){kind=icon}
.png){kind=icon}
Not logged in.png){kind=icon}
.png){kind=icon}
.png){kind=icon}
.png){kind=icon}
.png){kind=icon}
