Bi, Xia-An Xing, Zhaoxu Zhou, Wenyan Li, Lou Xu, Luyun
Published in
IEEE journal of biomedical and health informatics
Medical imaging technology and gene sequencing technology have long been widely used to analyze the pathogenesis and make precise diagnoses of mild cognitive impairment (MCI). However, few studies involve the fusion of radiomics data with genomics data to make full use of the complementarity between different omics to detect pathogenic factors of M...
Wang, Lin Yin, Zheng Puppala, Mamta Ezeana, Chika Wong, Kelvin He, Tiancheng Gotur, Deepa Wong, Stephen
Published in
IEEE journal of biomedical and health informatics
This paper presents a novel Lasso Logistic Regression model based on feature-based time series data to determine disease severity and when to administer drugs or escalate intervention procedures in patients with coronavirus disease 2019 (COVID-19). Advanced features were extracted from highly enriched and time series vital sign data of hospitalized...
Xing, Fangxu Liu, Xiaofeng Kuo, C-C Jay Fakhri, Georges El Woo, Jonghye
Published in
IEEE journal of biomedical and health informatics
Modeling statistical properties of anatomical structures using magnetic resonance imaging is essential for revealing common information of a target population and unique properties of specific subjects. In brain imaging, a statistical brain atlas is often constructed using a number of healthy subjects. When tumors are present, however, it is diffic...
Zhang, Huaqi Liu, Jie Wang, Pengyu Yu, Zekuan Liu, Weifan Chen, Huang
Published in
IEEE journal of biomedical and health informatics
Recent digital pathology workflows mainly focus on mono-modality histopathology image analysis. However, they ignore the complementarity between Haematoxylin & Eosin (H&E) and Immunohistochemically (IHC) stained images, which can provide comprehensive gold standard for cancer diagnosis. To resolve this issue, we propose a cross-boosted multi-target...
Kornaropoulos, Evgenios N Zacharaki, Evangelia I Zerbib, Pierre Lin, Chieh Rahmouni, Alain Paragios, Nikos
Published in
IEEE journal of biomedical and health informatics
The Apparent Diffusion Coefficient (ADC) is considered an importantimaging biomarker contributing to the assessment of tissue microstructure and pathophy- siology. It is calculated from Diffusion-Weighted Magnetic Resonance Imaging (DWI) by means of a diffusion model, usually without considering any motion during image acquisition. We propose a met...
Wang, Lei Li, Hao Wang, Yuqi Tan, Yihong Chen, Zhiping Pei, Tingrui Zou, Quan
Published in
IEEE journal of biomedical and health informatics
More and more evidence has demonstrated that microbiota play important roles in the life processes of the human body. In recent years, various computational methods have been proposed for identifying potentially disease-associated microbes to save costs in traditional biological experiments. However, prediction performances of these methods are gen...
Koss, Jonathan Tinaz, Sule Tagare, Hemant D
Published in
IEEE journal of biomedical and health informatics
Clinical scores (disease rating scales) are ordinal in nature. Longitudinal studies which use clinical scores produce ordinal time series. These time series tend to be noisy and often have a short-duration. This paper proposes a denoising method for such time series. The method uses a hierarchical approach to draw statistical power from the entire ...
Mieloszyk, Rebecca Twede, Hope Lester, Jonathan Wander, Jeremiah Basu, Sumit Cohn, Gabe Smith, Greg Morris, Dan Gupta, Sidhant Tan, Desney
...
Published in
IEEE journal of biomedical and health informatics
While non-invasive, cuffless blood pressure (BP) measurement has demonstrated relevancy in controlled environments, ambulatory measurement is important for hypertension diagnosis and control. We present both in-lab and ambulatory BP estimation results from a diverse cohort of participants. Participants (N=1125, aged 21-85, 49.2% female, multiple hy...
Nousias, George Panagiotopoulou, Eirini-Kanella Delibasis, Konstantinos Chaliasou, Aikaterini-Maria Tzounakou, Anastasia-Maria Labiris, Georgios
Published in
IEEE journal of biomedical and health informatics
Blink detection and classification can provide a very useful clinical indicator, because of its relation with many neurological and ophthalmological conditions. In this work, we propose a system that automatically detects and classifies blinks as "complete" or "incomplete" in high resolution image sequences zoomed into the participants' face, acqui...
Liao, Zhibin Liao, Kewen Shen, Haifeng van Boxel, Marouska F Prijs, Jasper Jaarsma, Ruurd L Doornberg, Job N Hengel, Anton van den Verjans, Johan W
Published in
IEEE journal of biomedical and health informatics
Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A common criticism of CNNs is their opaque learning and reasoning process, making it difficult to trust machine diagnosis and the subsequent adoption of such algorithms in clin...
