Results 81 to 90 of about 9,106,328 (402)

Bone Segmentation in Contrast Enhanced Whole-Body Computed Tomography [PDF]

arXiv, 2020
Segmentation of bone regions allows for enhanced diagnostics, disease characterisation and treatment monitoring in CT imaging. In contrast enhanced whole-body scans accurate automatic segmentation is particularly difficult as low dose whole body protocols reduce image quality and make contrast enhanced regions more difficult to separate when relying on
arxiv  

Evaluation of the primary anastomosis side effects in patients with sigmoid volvulus in Imam Hossein and Firoozgar Hospitals in 2014-2015

Journal of Acute Disease, 2017
Objective: The term volvulus is derived from a Latin word volvere means to turn, twist which is mainly referred to as twisting of sigmoid and can lead to ischemia and gangrene. Nowadays, it is the 3rd most common reason of bowel obstruction mostly in the
Mahdi Alemrajabi, Mostafa Hosseini, Behzad Nemati Honar, Mahdi Kayyal, Adnan Tizmaghz, Amirmohsen Jalaeefar   +5 more
doaj   +1 more source

Community-level Monitoring of HIV Spread [PDF]

, 2020
Health departments are using HIV data to monitor HIV growth in real time. The main purpose of this monitoring is to come up with policies for efficient allocation of medical resources.
Malekian, Sina
core  

Soft Bioelectronic Interfaces for Continuous Peripheral Neural Signal Recording and Robust Cross‐Subject Decoding

Advanced Science, EarlyView.
A soft poly (3,4‐ethylenedioxythiophene):poly (styrenesulfonate)‐based electrode enables continuous, high‐quality recording of peripheral nerve activity. A neural network model integrating handcrafted and convolutional neural network‐based features decodes whisker movements with strong generalization, offering insights into peripheral nerve function ...
Liangpeng Chen, Yang Liu, Yewei Huang, Ziyang Li, Chao Zhang, Jun Tang, Xueyuan Ling, Bowen Cao, Baowang Li, Yuan Zhang, Wenjianlong Zhou, Qin Xu, Shunchang Ma, Xiudong Guan, Dan Xiao, Jingyao Geng, Yutong Zhao, Guolin Li, Yi‐xuan Wang, Wang Jia, Yuanwen Jiang, Milin Zhang, Deling Li   +22 more
wiley   +1 more source

DeepCCDS: Interpretable Deep Learning Framework for Predicting Cancer Cell Drug Sensitivity through Characterizing Cancer Driver Signals

Advanced Science, EarlyView.
DeepCCDS leverages prior knowledge and self‐supervised learning to model cancer driver signals for drug sensitivity prediction. It captures complex regulatory patterns enabling more biologically informed representations. The framework outperforms existing methods across datasets, offering improved accuracy and interpretability.
Jiashuo Wu, Jiyin Lai, Xilong Zhao, Ziyi Wang, Yongbao Zhang, Liqiang Wang, Yinchun Su, Yalan He, Siyuan Li, Ying Jiang, Junwei Han   +10 more
wiley   +1 more source

Design and Development of Artificial Neural Networking (ANN) system using sigmoid activation function to predict annual rice production in Tamilnadu [PDF]

IJCSEIT, Vol.3, No.1, February 2013, 2013
Prediction of annual rice production in all the 31 districts of Tamilnadu is an important decision for the Government of Tamilnadu. Rice production is a complex process and non linear problem involving soil, crop, weather, pest, disease, capital, labour and management parameters.
arxiv  

Cerebral Venous Sinus Thrombosis and Posterior Reversible Encephalopathy Syndrome in a Preeclamptic Woman [PDF]

Journal of Clinical and Diagnostic Research, 2015
Cerebral venous sinus thrombosis (CVST) and posterior reversible encephalopathy syndrome (PRES) are two rare diseases which may present with similar symptoms and signs. We report a case with coexisting PRES and CVST in a preeclamptic woman.
Nadiye Köroglu, Sinem Sudolmus, Elif Asli Sarıoglu, Alpay Alkan, Ramazan Dansuk   +4 more
doaj   +1 more source

edge2vec: Representation learning using edge semantics for biomedical knowledge discovery

, 2019
Representation learning provides new and powerful graph analytical approaches and tools for the highly valued data science challenge of mining knowledge graphs.
Ding, Ying, Foote, Brian, Fu, Gang, Gao, Zheng, Gessner, Christopher, Liu, Xiaozhong, Ouyang, Chunping, Tsutsui, Satoshi, Wild, David, Yang, Jeremy, Yu, Qi   +10 more
core   +1 more source

Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites

Advanced Science, EarlyView.
Selective carbonylation sites (SCANS) are conceptualized, designed, evaluated, and released. SCANS captures segment‐level, protein‐level, and residue embeddings features. It utilizes elaborate loss function to penalize cross‐predictions at the residue level.
Jian Zhang, Jingjing Qian, Pei Wang, Xuan Liu, Fuhao Zhang, Haiting Chai, Quan Zou   +6 more
wiley   +1 more source

A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome [PDF]

arXiv, 2018
In this work, we consider the problem of predicting the course of a progressive disease, such as cancer or Alzheimer's. Progressive diseases often start with mild symptoms that might precede a diagnosis, and each patient follows their own trajectory.
arxiv