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A Proposed mHealth Intervention to Address Patient Barriers to Colposcopy Attendance: Qualitative Interview Study of Clinic Staff and Patient Perspectives.
JMIR Form Res
January 2025
Center for Cancer Health Equity, Rutgers Cancer Institute, New Brunswick, NJ, United States.
Background: Cervical cancer disparities persist among minoritized women due to infrequent screening and poor follow-up. Structural and psychosocial barriers to following up with colposcopy are problematic for minoritized women. Evidence-based interventions using patient navigation and tailored telephone counseling, including the Tailored Communication for Cervical Cancer Risk (TC3), have modestly improved colposcopy attendance.
View Article and Find Full Text PDFMulti-Modality Imaging in Cardio-Rheumatology.
Curr Cardiol Rep
January 2025
Onassis Cardiac Surgery Center, Athens, Greece.
Purpose Of Review: Our purpose was to discuss the advantages and disadvantages of various noninvasive imaging modalities in the evaluation of cardiovascular disease (CVD) in patients with autoimmune rheumatic diseases (ARDs). The detailed knowledge of imaging modalities will facilitate the diagnosis and follow up of CVD in ARDs.
Recent Findings: Autoimmune Rheumatic Diseases (ARDs) are characterized by alterations in immunoregulatory system of the body.
A Machine Learning Model Using Cardiac CT and MRI Data Predicts Cardiovascular Events in Obstructive Coronary Artery Disease.
Radiology
January 2025
From the Department of Cardiology (T.P., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), MIRACL.ai (Multimodality Imaging for Research and Analysis Core Laboratory: and Artificial Intelligence) (T.P., S.T., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), Inserm MASCOT-UMRS 942 (T.P., K.H., T.A.S., T.G., A.L., E.G., A.U., J.G.D., P.H.), and Department of Radiology (T.P., V.B., L.H., T.G.), Université Paris Cité, University Hospital of Lariboisière, Assistance Publique-Hôpitaux de Paris, Paris, France; Cardiovascular Magnetic Resonance Laboratory (T.P., T.H., T.U., F.S., S.C., P.G., J.G.) and Cardiac Computed Tomography Laboratory (T.P., T.H., T.L., B.C., T.U., F.S., S.C., H.B., A.N., M.A., P.G., J.G.), Hôpital Privé Jacques Cartier, Institut Cardiovasculaire Paris Sud, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300 Massy, France; Scientific Partnerships, Siemens Healthcare France, Saint-Denis, France (S.T.); Department of Cardiology, Hôpital Universitaire de Bruxelles-Hôpital Erasme, Brussels, Belgium (A.U.); and Department of Cardiovascular Imaging, American Hospital of Paris, Neuilly, France (O.V., M.S.).
Background Multimodality imaging is essential for personalized prognostic stratification in suspected coronary artery disease (CAD). Machine learning (ML) methods can help address this complexity by incorporating a broader spectrum of variables. Purpose To investigate the performance of an ML model that uses both stress cardiac MRI and coronary CT angiography (CCTA) data to predict major adverse cardiovascular events (MACE) in patients with newly diagnosed CAD.
View Article and Find Full Text PDFAn empirical study of LLaMA3 quantization: from LLMs to MLLMs.
Vis Intell
December 2024
Department of Information Technology and Electrical Engineering, ETH Zurich, Sternwartstrasse 7, Zürich, Switzerland.
The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language models (MLLMs), widely used in computer vision and natural language understanding tasks. In particular, LLaMA3 models have recently been released and have achieved impressive performance in various domains with super-large scale pre-training on over 15T tokens of data. Given the wide application of low-bit quantization for LLMs in resource-constrained scenarios, we explore LLaMA3's capabilities when quantized to low bit-width.
View Article and Find Full Text PDFDeep learning radiomics analysis for prediction of survival in patients with unresectable gastric cancer receiving immunotherapy.
Eur J Radiol Open
June 2025
Department of Medical Oncology, The Fifth Medical Center, Chinese People's Liberation Army General Hospital, Beijing, PR China.
Objective: Immunotherapy has become an option for the first-line therapy of advanced gastric cancer (GC), with improved survival. Our study aimed to investigate unresectable GC from an imaging perspective combined with clinicopathological variables to identify patients who were most likely to benefit from immunotherapy.
Method: Patients with unresectable GC who were consecutively treated with immunotherapy at two different medical centers of Chinese PLA General Hospital were included and divided into the training and validation cohorts, respectively.
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