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Augmented prediction of vertebral collapse after osteoporotic vertebral compression fractures through parameter-efficient fine-tuning of biomedical foundation models.
Sci Rep
December 2024
Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.
View Article and Find Full Text PDFBidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.
Sci Rep
December 2024
School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Petaling Jaya, 47500, Selangor Darul Ehsan, Malaysia.
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence.
View Article and Find Full Text PDFWeb application using machine learning to predict cardiovascular disease and hypertension in mine workers.
Sci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
View Article and Find Full Text PDFApplication of green silver nano-particles as anti-bacterial and photo-catalytic degradation of azo dye in wastewater.
Sci Rep
December 2024
Sustainability Solutions Research Lab, Faculty of Engineering, University of Pannonia, Egyetem Str. 10, Veszprém, 8200, Hungary.
Ensuring everyone enjoys healthy lifestyles and well-being at all ages, Progress has been made in increasing access to clean water and sanitation facilities and reducing the spread of epidemics and diseases. The synthesis of nano-particles (NPs) by using microalgae is a new nanobiotechnology due to the use of the biomolecular (corona) of microalgae as a capping and reducing agent for NP creation. This investigation explores the capacity of a distinct indigenous microalgal strain to synthesize silver nano-particles (AgNPs), as well as its effectiveness against multi-drug resistant (MDR) bacteria and its ability to degrade Azo dye (Methyl Red) in wastewater.
View Article and Find Full Text PDFFast and sensitive multivalent spatial pattern-recognition for circular RNA detection.
Nat Commun
December 2024
Department of Pharmacology, Jiangsu Provincial Key Laboratory of Critical Care Medicine, School of Medicine, Southeast University, Nanjing, China.
While circular RNAs (circRNAs) exhibit lower abundance compared to corresponding linear RNAs, they demonstrate potent biological functions. Nevertheless, challenges arise from the low concentration and distinctive structural features of circRNAs, rendering existing methods operationally intricate and less sensitive. Here, we engineer an intelligent tetrahedral DNA framework (TDF) possessing precise spatial pattern-recognition properties with exceptional sensing speed and sensitivity for circRNAs.
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