AIMC Topic: Lymphoma
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Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.
Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc
Oct 3, 2016
Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. ...
Automatic negation detection in narrative pathology reports.
Artificial intelligence in medicine
Mar 24, 2015
OBJECTIVE: To detect negations of medical entities in free-text pathology reports with different approaches, and evaluate their performances.
Simultaneous determination of 7 thiols associated proteins in lymphoma patients'serum and cerebrospinal fluid by UHPLC-HRMS technique.
Scientific reports
Jul 3, 2025
Thiol compounds can serve as markers for the antioxidant and prognostic status of lymphoma, playing a crucial role in early tumor diagnosis. However, their high polarity and lack of chromophores pose challenges for multivariate analysis. This study a...
[A deep learning method for differentiating nasopharyngeal carcinoma and lymphoma based on MRI].
Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery
Jul 1, 2025
To development a deep learning（DL） model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma（NPC） and nasopharyngeal lymphoma（NPL）. The retrospective study included 142 patients with NPL and 292...
Artificial intelligence based malignant lymphoma type prediction using enhanced super resolution image and hybrid feature extraction algorithm.
Computers in biology and medicine
Jul 1, 2025
In the medical field, the most common and frequent type of blood cancer is lymphoma. Accurately predicting and early response to lymphoma treatment will be useful for initiating treatment plans to achieve a greater rate of cure or reduced risk of tre...
Multi-class brain malignant tumor diagnosis in magnetic resonance imaging using convolutional neural networks.
Brain research bulletin
Jun 1, 2025
Glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and brain metastases (BM) are common malignant brain tumors with similar radiological features, while the accurate and non-invasive dialgnosis is essential for selecting appropriate...
Blood-brain barrier crossing biopolymer targeting c-Myc and anti-PD-1 activate primary brain lymphoma immunity: Artificial intelligence analysis.
Journal of controlled release : official journal of the Controlled Release Society
May 10, 2025
Primary Central Nervous System Lymphoma is an aggressive central nervous system neoplasm with poor response to pharmacological treatment, partially due to insufficient drug delivery across blood-brain barrier. In this study, we developed a novel ther...
Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.
World journal of gastroenterology
Jul 7, 2024
BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease (CD) is a challenge in clinical practice.
Application of Machine-learning based on Radiomics Features in Differential Diagnosis of Superficial Lymphadenopathy.
Current medical imaging
Jan 1, 2024
OBJECTIVE: The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method for distinguishing benign lymph nodes, lymphoma, and metastatic lymph nodes.
Prediction of sentinel lymph node metastasis in breast cancer by using deep learning radiomics based on ultrasound images.
Medicine
Nov 3, 2023
Sentinel lymph node metastasis (SLNM) is a crucial predictor for breast cancer treatment and survival. This study was designed to propose deep learning (DL) models based on grayscale ultrasound, color Doppler flow imaging (CDFI), and elastography ima...
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