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Prospective validation study of a combined urine and plasma test for predicting high-grade prostate cancer in biopsy naïve men.
Scand J Urol
January 2025
Department of Urology, Odense University Hospital, Odense, Denmark; Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
Objective: Early and accurate diagnosis of prostate cancer (PC) is crucial for effective treatment. Diagnosing clinically insignificant cancers can lead to overdiagnosis and overtreatment, highlighting the importance of accurately selecting patients for further evaluation based on improved risk prediction tools. Novel biomarkers offer promise for enhancing this diagnostic process.
View Article and Find Full Text PDFIdentification of IGFBP3 and LGALS1 as potential secreted biomarkers for clear cell renal cell carcinoma based on bioinformatics analysis and machine learning.
Adv Clin Exp Med
January 2025
Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, USA.
Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Due to the lack of symptoms until advanced stages, early diagnosis of ccRCC is challenging. Therefore, the identification of novel secreted biomarkers for the early detection of ccRCC is urgently needed.
View Article and Find Full Text PDFComparative evaluation of two dose-volume histogram prediction tools for treatment planning: Treatment planning quality and dose verification accuracy.
Tech Innov Patient Support Radiat Oncol
March 2025
Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Tokushima 770-8503, Japan.
Purpose: This study aims to compare treatment plans created using RapidPlan and PlanIQ for twelve patients with prostate cancer, focusing on dose uniformity, dose reduction to organs at risk (OARs), plan complexity, and dose verification accuracy. The goal is to identify the tool that demonstrates superior performance in achieving uniform target dose distribution and reducing OAR dose, while ensuring accurate dose verification.
Methods: Dose uniformity in the planning target volume, excluding the rectum, and dose reduction in the OARs (the rectum and bladder) were assessed.
Comparison of precision of implant placement between two different guided systems for static computer-assisted implant surgery: A simulation-based experimental study.
J Dent Sci
December 2024
Faculty of Dentistry, Department of Oral and Maxillofacial Surgery, Chulalongkorn University, Bangkok, Thailand.
Background/purpose: Many designs of static computer-assisted implant surgery (sCAIS) are available for clinician to achieve proper implant position. However, there were not any studies that approached the design alone to evaluate whether sleeve-in-sleeve or sleeve-on-drill design provided most accuracy implant position. The purpose of this study was to investigate the precision of implant placement with sleeve-in-sleeve and sleeve-on-drill static computer assisted implant surgery (sCAIS) designs.
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.
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