Search Results - "Pearson, Alexander T."

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer by Kather, Jakob Nikolas, Pearson, Alexander T., Halama, Niels, Jäger, Dirk, Krause, Jeremias, Loosen, Sven H., Marx, Alexander, Boor, Peter, Tacke, Frank, Neumann, Ulf Peter, Grabsch, Heike I., Yoshikawa, Takaki, Brenner, Hermann, Chang-Claude, Jenny, Hoffmeister, Michael, Trautwein, Christian, Luedde, Tom

“…Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice,…”
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Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers by Gao, Catherine A., Howard, Frederick M., Markov, Nikolay S., Dyer, Emma C., Ramesh, Siddhi, Luo, Yuan, Pearson, Alexander T.

“…Large language models such as ChatGPT can produce increasingly realistic text, with unknown information on the accuracy and integrity of using these models in…”
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The impact of site-specific digital histology signatures on deep learning model accuracy and bias by Howard, Frederick M., Dolezal, James, Kochanny, Sara, Schulte, Jefree, Chen, Heather, Heij, Lara, Huo, Dezheng, Nanda, Rita, Olopade, Olufunmilayo I., Kather, Jakob N., Cipriani, Nicole, Grossman, Robert L., Pearson, Alexander T.

“…The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict…”
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Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning by Echle, Amelie, Grabsch, Heike Irmgard, Quirke, Philip, van den Brandt, Piet A., West, Nicholas P., Hutchins, Gordon G.A., Heij, Lara R., Tan, Xiuxiang, Richman, Susan D., Krause, Jeremias, Alwers, Elizabeth, Jenniskens, Josien, Offermans, Kelly, Gray, Richard, Brenner, Hermann, Chang-Claude, Jenny, Trautwein, Christian, Pearson, Alexander T., Boor, Peter, Luedde, Tom, Gaisa, Nadine Therese, Hoffmeister, Michael, Kather, Jakob Nikolas

“…Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect…”
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Classical mathematical models for prediction of response to chemotherapy and immunotherapy by Ghaffari Laleh, Narmin, Loeffler, Chiara Maria Lavinia, Grajek, Julia, Staňková, Kateřina, Pearson, Alexander T, Muti, Hannah Sophie, Trautwein, Christian, Enderling, Heiko, Poleszczuk, Jan, Kather, Jakob Nikolas

“…Classical mathematical models of tumor growth have shaped our understanding of cancer and have broad practical implications for treatment scheduling and…”
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Machine Learning-Guided Adjuvant Treatment of Head and Neck Cancer by Howard, Frederick Matthew, Kochanny, Sara, Koshy, Matthew, Spiotto, Michael, Pearson, Alexander T

“…Postoperative chemoradiation is the standard of care for cancers with positive margins or extracapsular extension, but the benefit of chemotherapy is unclear…”
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Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary by Srisuwananukorn, Andrew, Salama, Mohamed E, Pearson, Alexander T

“…Deep learning (DL) is a subdomain of artificial intelligence algorithms capable of automatically evaluating subtle graphical features to make highly accurate…”
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Ovarian Carcinoma‐Associated Mesenchymal Stem Cells Arise from Tissue‐Specific Normal Stroma by Coffman, Lan G., Pearson, Alexander T., Frisbie, Leonard G., Freeman, Zachary, Christie, Elizabeth, Bowtell, David D., Buckanovich, Ronald J.

“…Carcinoma‐associated mesenchymal stem cells (CA‐MSCs) are critical stromal progenitor cells within the tumor microenvironment (TME). We previously demonstrated…”
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Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology by Dolezal, James M., Srisuwananukorn, Andrew, Karpeyev, Dmitry, Ramesh, Siddhi, Kochanny, Sara, Cody, Brittany, Mansfield, Aaron S., Rakshit, Sagar, Bansal, Radhika, Bois, Melanie C., Bungum, Aaron O., Schulte, Jefree J., Vokes, Everett E., Garassino, Marina Chiara, Husain, Aliya N., Pearson, Alexander T.

“…A model’s ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are…”
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Machine learning can identify newly diagnosed patients with CLL at high risk of infection by Agius, Rudi, Brieghel, Christian, Andersen, Michael A., Pearson, Alexander T., Ledergerber, Bruno, Cozzi-Lepri, Alessandro, Louzoun, Yoram, Andersen, Christen L., Bergstedt, Jacob, von Stemann, Jakob H., Jørgensen, Mette, Tang, Man-Hung Eric, Fontes, Magnus, Bahlo, Jasmin, Herling, Carmen D., Hallek, Michael, Lundgren, Jens, MacPherson, Cameron Ross, Larsen, Jan, Niemann, Carsten U.

“…Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and…”
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Slideflow: deep learning for digital histopathology with real-time whole-slide visualization by Dolezal, James M, Kochanny, Sara, Dyer, Emma, Ramesh, Siddhi, Srisuwananukorn, Andrew, Sacco, Matteo, Howard, Frederick M, Li, Anran, Mohan, Prajval, Pearson, Alexander T

“…Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and…”
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A nanoengineered topical transmucosal cisplatin delivery system induces anti-tumor response in animal models and patients with oral cancer by Goldberg, Manijeh, Manzi, Aaron, Birdi, Amritpreet, Laporte, Brandon, Conway, Peter, Cantin, Stefanie, Mishra, Vasudha, Singh, Alka, Pearson, Alexander T., Goldberg, Eric R., Goldberger, Sam, Flaum, Benjamin, Hasina, Rifat, London, Nyall R., Gallia, Gary L., Bettegowda, Chetan, Young, Simon, Sandulache, Vlad, Melville, James, Shum, Jonathan, O’Neill, Sonya E., Aydin, Erkin, Zhavoronkov, Alex, Vidal, Anxo, Soto, Atenea, Alonso, Maria Jose, Rosenberg, Ari J., Lingen, Mark W., D’Cruz, Anil, Agrawal, Nishant, Izumchenko, Evgeny

“…Despite therapeutic advancements, oral cavity squamous cell carcinoma (OCSCC) remains a difficult disease to treat. Systemic platinum-based chemotherapy often…”
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A mathematical model for IL-6-mediated, stem cell driven tumor growth and targeted treatment by Nazari, Fereshteh, Pearson, Alexander T, Nör, Jacques Eduardo, Jackson, Trachette L

“…Targeting key regulators of the cancer stem cell phenotype to overcome their critical influence on tumor growth is a promising new strategy for cancer…”
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Mathematical model predicts tumor control patterns induced by fast and slow cytotoxic T lymphocyte killing mechanisms by Wang, Yixuan, Bergman, Daniel R, Trujillo, Erica, Pearson, Alexander T., Sweis, Randy F., Jackson, Trachette L.

“…Immunotherapy has dramatically transformed the cancer treatment landscape largely due to the efficacy of immune checkpoint inhibitors (ICIs). Although ICIs…”
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The IL-6R and Bmi-1 axis controls self-renewal and chemoresistance of head and neck cancer stem cells by Herzog, Alexandra E., Warner, Kristy A., Zhang, Zhaocheng, Bellile, Emily, Bhagat, Meera A., Castilho, Rogerio M., Wolf, Gregory T., Polverini, Peter J., Pearson, Alexander T., Nör, Jacques E.

“…Despite major progress in elucidating the pathobiology of head and neck squamous cell carcinoma (HNSCC), the high frequency of disease relapse correlates with…”
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Artificial Intelligence Can Cut Costs While Maintaining Accuracy in Colorectal Cancer Genotyping by Kacew, Alec J, Strohbehn, Garth W, Saulsberry, Loren, Laiteerapong, Neda, Cipriani, Nicole A, Kather, Jakob N, Pearson, Alexander T

“…Rising cancer care costs impose financial burdens on health systems. Applying artificial intelligence to diagnostic algorithms may reduce testing costs and…”
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AL101, a gamma-secretase inhibitor, has potent antitumor activity against adenoid cystic carcinoma with activated NOTCH signaling by Ferrarotto, Renata, Mishra, Vasudha, Herz, Elad, Yaacov, Adar, Solomon, Oz, Rauch, Rami, Mondshine, Adi, Motin, Maria, Leibovich-Rivkin, Tal, Davis, Matti, Kaye, Joel, Weber, Christopher R., Shen, Le, Pearson, Alexander T., Rosenberg, Ari J., Chen, Xiangying, Singh, Alka, Aster, Jon C., Agrawal, Nishant, Izumchenko, Evgeny

“…Adenoid cystic carcinoma (ACC) is an aggressive salivary gland malignancy with limited treatment options for recurrent or metastatic disease. Due to…”
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Machine learning for detection and classification of oral potentially malignant disorders: A conceptual review by Souza, Lucas Lacerda, Fonseca, Felipe Paiva, Araújo, Anna Luiza Damaceno, Lopes, Marcio Ajudarte, Vargas, Pablo Agustin, Khurram, Syed Ali, Kowalski, Luiz Paulo, Santos, Harim Tavares, Warnakulasuriya, Saman, Dolezal, James, Pearson, Alexander T., Santos‐Silva, Alan Roger

“…Oral potentially malignant disorders represent precursor lesions that may undergo malignant transformation to oral cancer. There are many known risk factors…”
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Dysregulated FGFR3 signaling alters the immune landscape in bladder cancer and presents therapeutic possibilities in an agent-based model by Bergman, Daniel R, Wang, Yixuan, Trujillo, Erica, Fernald, Anthony A, Li, Lie, Pearson, Alexander T, Sweis, Randy F, Jackson, Trachette L

“…Bladder cancer is an increasingly prevalent global disease that continues to cause morbidity and mortality despite recent advances in treatment. Immune…”
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Extracellular matrix alignment dictates the organization of focal adhesions and directs uniaxial cell migration by Wang, William Y., Pearson, Alexander T., Kutys, Matthew L., Choi, Colin K., Wozniak, Michele A., Baker, Brendon M., Chen, Christopher S.

“…Physical features of the extracellular matrix (ECM) heavily influence cell migration strategies and efficiency. Migration in and on fibrous ECMs is of…”
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