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In this paper we have presented an automated diagnosis of breast cell cancer using histopathological images on the basis of different textural descriptors. In the proposed technique, the images being preprocessed using extended adaptive-top-bottom transform (EAHE-TBhat) and segmented the nuclei regions from the non-nuclei regions using region growing segmentation. The nuclei regions are then used...
Pairwise protein structure comparison has taken significant scientific research effort in last two decades. Even though it all started with alignment-based comparison methods, recently there are several non-alignment based methods that have shown good potential. One such approach is based on shape descriptors. These methods use histograms or vectors to represent the molecular shapes. They have shown...
Natural Language Processing and Machine Learning techniques can be used to automatically identify, extract and manipulate textual clinical data. Many of these methods are strongly dependent on annotated corpora that are very difficult to find in the clinical domain, especially for the Brazilian Portuguese language. The annotation task is expensive and time-consuming; hence, it is important to provide...
We consider the problem of partitioning clinical services in hospitals into groups with the goal of efficiently allocating existing inpatient beds. At the strategic level, there are two major possibilities: pooling versus focusing. Pooling the bed capacity allows one to achieve an overall high occupancy level for a fixed number of beds. On the other hand, focusing by dividing the capacity into groups...
Classification models have proven useful for predicting clinical interventions and patient outcomes. One of the key issues that affect the predictive ability of supervised learning frameworks in the healthcare scenario is imbalance in data sets. In addition, non-uniform data collection processes in clinical scenarios lead to poor quality data sets. We designed a novel approach to predict Intensive...
In medical care, it is essential to assess and manage acute painful conditions adequately. Heart rate variability (HRV) analysis is based on the acquisition of electrocardiogram (ECG), which is available from both patient monitor and wearable device. As HRV analysis can reflect autonomic nervous system activity which is unconsciously regulated, HRV analysis in ultra-short-term is getting attention...
Breast cancer is one of the major causes of death among women around the world. To diagnose this disease using mammography technique, segmentation is an important step to detect the suspicious region(s) of mammograms. Segmentation concerns to the process of division of mammograms into different sections. Objective of segmentation is to simply modify the presentation of an image so that it becomes...
The complexity of biological data is a difficult challenge for data integration. Thus, this study develops a localized web service platform for the specific bioinformatics study needs of Southwest University of China. Our platform includes the following three innovation features, (1) Graphical Survival time analysis kit; (2) Codon Deviation Coefficient (CDC) computing kit and (3) Long non-coding RNA...
As the diagnosis of lung cancer, lung mass for the diagnosis of the disease is meaningful, chest radiography has low price, low radiation, popularity and other characteristics, it is a significant attempt for the location of chest masses on chest radiography using deep learning method. In this paper we have established a labeled lung mass database, and presented a state of the art deep learning methodology...
Identifying and evaluating functionally connected regions in the brain has become a challenging problem to solve in many studies of neurological and psychiatric disorders. In particular, functional connectivity of brain mechanisms underlying disturbed cognition in depression is still not well understood in current neuroscience research. Based on the Stroop paradigm, specifically, the face-word Stroop...
Solid state fermentation processes are mediated by the collective metabolism of specialized microbial communities. Monitoring the relative abundance of dominating species is a critical task in quality control, which is traditionally done by wet lab techniques, such as quantitative PCR (qPCR). In this study, we developed a computational method to quantify microbial species in metagenomes based on their...
We consider the problem of predicting three procedures, viz, EKG, Angioplasty and Valve Replacement procedures jointly from Electronic Health Records (EHR) and develop a discriminative boosted Bayesian network algorithm. Differences between our proposed approach and standard Bayes Net structure learners are (1) we do not assume that the number of features (observations) are uniform across training...
This work describes a new dataset to improve pedometer evaluation. Prior evaluation techniques focus on regular gaits using laboratory assessment to simplify the manual counting of actual steps. Our goal is to analyze pedometer algorithms under more natural conditions that occur during daily living where gaits are frequently changing or remain regular for only brief periods of time. We video recorded...
This study proposes a new approach called Medi-Deep (Deep Control in a Medication Usage). Medi-Deep is based on a remote management technology that aims to be in a reliable and a solid position while information amongst a patient and a doctor are being exchanged. Nowadays, most of the people do not follow their prescribed medications because of having a busy life, a memory problem, or/and a laziness...
Stroke is a leading cause of long-term adult disability. Stroke patients can recover through rehabilitation programs prescribed by occupational therapists (OT); however, an individualized rehabilitation program can reduce recovery times compared to traditional ones. In this paper, we propose a daily activity observation system (DAOS) that uses a Kinect v2 sensor to collect and retrieve motion data...
Clinical Decision Support (CDS) can be regarded as an information retrieval (IR) task, where medical records are used to retrieve the full-text biomedical articles to satisfy the information needs from physicians, aiming at better medical solutions. Recent attempts have introduced the advances of deep learning by employing neural IR methods for CDS, where, however, only the document-query relationship...
Soybean tissue-specific network helps identify and visualize the gene-gene relationships in various tissues [1]. We have built SoyTSN, a web-based tool for tissue-specific network prediction in soybean using 14 tissues RNA-Seq datasets including flower, root, nodule, leaf, stem, seed, etc. SoyTSN first combines multiple tissue specific RNA-Seq studies, and later Cross-Conditions Cluster Detection...
In microarray/RNAseq experiments, different samples used in the same experiment may have significant levels of heterogeneity. Here, heterogeneity refers to the unique temporospatial composition of various cells in different samples. Consequently, the experimental results and subsequent data analysis may be seriously biased. To minimize the influence of heterogeneous samples in data analysis, the first...
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Protein crystallization is the process of formation of protein crystals. Many combinations of chemicals need to be tried to obtain a crystal for some difficult proteins. This paper discusses a novel way of identifying the various conditions necessary for a successful crystal growth by using a variation of genetic algorithm which explores unexplored territories of the chemical search space, thereby...
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