Disclosures: xiangnan teng: Nothing to Disclose, Jin Shang: Nothing to Disclose, Lingyao Du: Nothing to Disclose, hong Tang: Nothing to Disclose, Lang Bai: Nothing to Disclose 1826 A CLINICOPATHOLOGICAL AND ARTIFICIAL INTELLIGENCE-DERIVED SCREENING MODEL AS A TOOL FOR DISTINGUISHING PATIENTS WITH NON-HODGKIN LYMPHOMAS FROM INFLAMMATORY HEPATIC DISEASES: A MULTICENTRIC LEARNING APPROACH Mina Farag 1 Andre Lametti 1 Ajay Rajaram 1 Nadine Demko 1 Pari Jafari 2 Ruoji Zhou 3 Alison Xiaotang Du 3 Pierre Fiset 1 Amine Benmassaoud 4 Farhad Maleki 5 Victoria Marcus 1 Rene P MICHEL 1 Amy Chadburn 6 John Hart 2 Greta Evaristo 7 , 1 McGill University, 2 University of Chicago, 3 UCLA Medical Center, 4 McGill Univertsity, 5 University of Calgary, 6 Weill Cornell Medicine, 7 McGill Univeristy Background: Primary hepatic non-Hodgkin lymphomas (NHL) are rare, with nonspecific and often subtle clinical presentations
Consequently, the identification of novel molecular targets and the development of innovative treatment modalities aimed at slowing progression and alleviating symptoms represent pressing priorities within AD clinical research
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Homogenates were then centrifuged for 15 min at 9,600 x g at 4C and supernatants were collected
Its essential for anyone with underlying health conditions to consult with a healthcare provider to determine if B12 injections are safe and appropriate for their specific needs
