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Urgency Prediction for Medical Laboratory Tests Through Optimal Sparse Decision Tree: Case Study With Echocardiograms.
JMIR AI
January 2025
Department of Information Systems and Business Analytics, Iowa State University, Ames, IA, United States.
Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care.
View Article and Find Full Text PDFAccurate Standard Siren Cosmology with Joint Gravitational-Wave and γ-Ray Burst Observations.
Phys Rev Lett
December 2024
Université de Genève, Département de Physique Théorique and Gravitational Wave Science Center (GWSC), 24 quai Ernest Ansermet, 1211 Genève 4, Switzerland.
Joint gravitational-wave and γ-ray burst (GRB) observations are among the best prospects for standard siren cosmology. However, the strong selection effect for the coincident GRB detection, which is possible only for sources with small inclination angles, induces a systematic uncertainty that is currently not accounted for. We show that this severe source of bias can be removed by inferring the a priori unknown electromagnetic detection probability directly from multimessenger data.
View Article and Find Full Text PDFGenerative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.
Eur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
Gold nanocomposites in colorectal cancer therapy: characterization, selective cytotoxicity, and migration inhibition.
Naunyn Schmiedebergs Arch Pharmacol
January 2025
Department of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, UCSI University, No. 1, Jalan Menara Gading, Taman Connaught, Cheras, Kuala Lumpur, 56000, Malaysia.
The third most prevalent type of cancer in the world, colorectal cancer, poses a significant treatment challenge due to the nonspecific distribution, low efficacy, and high systemic toxicity associated with chemotherapy. To overcome these limitations, a targeted drug delivery system with a high cytotoxicity against cancer cells while maintaining a minimal systemic side effects represents a promising therapeutic approach. Therefore, the aim of this study was to develop an efficient gold nanocarrier for the targeted delivery of the anticancer agent everolimus to Caco-2 cells.
View Article and Find Full Text PDFPhyto-mediated fabrication of silver nanoparticles from Scrophularia striata extract (AgNPs-SSE): a potential inducer of apoptosis in breast cancer cells.
Mol Biol Rep
January 2025
Department of Biology, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Background: Breast carcinoma stands out as the most widespread invasive cancer and the top contributor to cancer-related mortality in women. Nanoparticles have emerged as promising tools in cancer detection, diagnosis, and prevention. In this study, the antitumor and apoptotic capability of silver nanoparticles synthesized through Scrophularia striata extract (AgNPs-SSE) was investigated toward breast cancer cells.
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