Search results for "Medical Informatics"
showing 10 items of 359 documents
Recent advances in machine learning for maximal oxygen uptake (VO2 max) prediction : A review
2022
Maximal oxygen uptake (VO2 max) is the maximum amount of oxygen attainable by a person during exercise. VO2 max is used in different domains including sports and medical sciences and is usually measured during an incremental treadmill or cycle ergometer test. The drawback of directly measuring VO2 max using the maximal test is that it is expensive and requires a fixed and controlled protocol. During the last decade, various machine learning models have been developed for VO2 max prediction and numerous studies have attempted to predict VO2 max using data from submaximal and non-exercise tests. This article gives an overview of the machine learning models developed over the past five years (…
Altered neural responses to social fairness in bipolar disorder
2020
Highlights • Bipolar disorder is characterized by impaired processing of social fairness. • BD patients exhibit increased rejection of moderate unfairness in Ultimatum Game. • BD patients display decreased response to moderate unfairness in anterior insula. • BD patients deactivate posterior and middle insula in response to unfairness. • Trait impulsivity positively correlated with deactivations in posterior insula.
FASTA/Q data compressors for MapReduce-Hadoop genomics: space and time savings made easy
2021
Abstract Background Storage of genomic data is a major cost for the Life Sciences, effectively addressed via specialized data compression methods. For the same reasons of abundance in data production, the use of Big Data technologies is seen as the future for genomic data storage and processing, with MapReduce-Hadoop as leaders. Somewhat surprisingly, none of the specialized FASTA/Q compressors is available within Hadoop. Indeed, their deployment there is not exactly immediate. Such a State of the Art is problematic. Results We provide major advances in two different directions. Methodologically, we propose two general methods, with the corresponding software, that make very easy to deploy …
Can google trends and wikipedia help traditional surveillance? A pilot study on measles
2019
Introduction: Cases of measles in some European countries are increasing. The aim of this study is to find the correlation between Google Trends and Wikipedia searches and the real number of cases notified. Materials and Methods: The data on Internet searches have been obtained from Google Trends and Wikipedia. The reported cases of measles were selected from January 2013 until December 2018 for Google Trends and July 2015 until December 2018 from for Wikipedia. We have selected data from four European Countries: Italy, France, Germany and Romania. The data extracted from Wikipedia and Google Trends have been moved over time (Lag), one month in the future and one month in the past. Cross-co…
Digital epidemiology: assessment of measles infection through Google Trends mechanism in Italy.
2019
Introduction. The primary aim of this study is to evaluate the temporal correlation between Google Trends and the data on measles infection arising from the conventional surveillance system, reported by the Istituto Superiore di Sanità's (ISS) bulletin. Moreover, this study is also aimed at forecasting the trends of the reported infectious diseases cases over time. Materials and Methods. The reported cases of measles were selected from January 2013 until October 2018. The data on Internet searches have been obtained from Google Trends; the research data referred to the first 48 weeks of year 2017 have been aggregated on a weekly basis. The search volume provided by Google Trends has a relat…
Radiomics and Prostate MRI: Current Role and Future Applications
2021
Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine …
A motif-independent metric for DNA sequence specificity
2011
Abstract Background Genome-wide mapping of protein-DNA interactions has been widely used to investigate biological functions of the genome. An important question is to what extent such interactions are regulated at the DNA sequence level. However, current investigation is hampered by the lack of computational methods for systematic evaluating sequence specificity. Results We present a simple, unbiased quantitative measure for DNA sequence specificity called the Motif Independent Measure (MIM). By analyzing both simulated and real experimental data, we found that the MIM measure can be used to detect sequence specificity independent of presence of transcription factor (TF) binding motifs. We…
Benefits and Threats to Using Social Media for Presenting and Implementing Evidence.
2018
As a potential high-yield tool for disseminating information that can reach many people, social media is transforming how clinicians, the public, and policy makers are educated and find new knowledge associated with research-related information. Social media is available to all who access the internet, reducing selected barriers to acquiring original source documents such as journal articles or books and potentially improving implementation-the process of formulating a conclusion and moving on that decision. The use of social media for evidence dissemination/implementation of research has both benefits and threats. It is the aim of this Viewpoint to provide a balanced view of each. J Orthop…
Variable-order reference-free variant discovery with the Burrows-Wheeler Transform
2020
Abstract Background In [Prezza et al., AMB 2019], a new reference-free and alignment-free framework for the detection of SNPs was suggested and tested. The framework, based on the Burrows-Wheeler Transform (BWT), significantly improves sensitivity and precision of previous de Bruijn graphs based tools by overcoming several of their limitations, namely: (i) the need to establish a fixed value, usually small, for the order k, (ii) the loss of important information such as k-mer coverage and adjacency of k-mers within the same read, and (iii) bad performance in repeated regions longer than k bases. The preliminary tool, however, was able to identify only SNPs and it was too slow and memory con…
Deep Neural Networks for Prediction of Exacerbations of Patients with Chronic Obstructive Pulmonary Disease
2018
Chronic Obstructive Pulmonary Disease (COPD) patients need help in daily life situations as they are burdened with frequent risks of acute exacerbation and loss of control. An automated monitoring system could lead to timely treatments and avoid unnecessary hospital (re-)admissions and home visits by doctors or nurses. Therefore we present a Deep Artificial Neural Networks for approach prediction of exacerbations, particularly Feed-Forward Neural Networks (FFNN) for classification of COPD patients category and Long Short-Term Memory (LSTM), for early prediction of COPD exacerbations and subsequent triage. The FFNN and LSTM models are trained on data collected from remote monitoring of 94 pa…