20,919 results match your criteria learning selection

Fertility Knowledge and Awareness Practices.

Nurs Womens Health 2021 May 4. Epub 2021 May 4.

Objective: To synthesize the literature on fertility knowledge and fertility awareness among women seeking pregnancy.

Data Sources: The search terms "fertility awareness OR fertility knowledge AND women AND subfertile OR infertile OR seeking pregnancy OR trying to conceive OR pre-conception OR conception NOT contraception NOT birth control" were used via CINAHL, PubMed, and Web of Science. Primary research studies were considered in the search parameters. Read More

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A New Sequential Forward Feature Selection (SFFS) Algorithm for Mining Best Topological and Biological Features to Predict Protein Complexes from Protein-Protein Interaction Networks (PPINs).

Interdiscip Sci 2021 May 6. Epub 2021 May 6.

Department of Computer Science, COMSATS University Islamabad, Lahore, Pakistan.

Protein-protein interaction plays an important role in the understanding of biological processes in the body. A network of dynamic protein complexes within a cell that regulates most biological processes is known as a protein-protein interaction network (PPIN). Complex prediction from PPINs is a challenging task. Read More

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Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities.

Front Genet 2021 20;12:669328. Epub 2021 Apr 20.

The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot, China.

Antimicrobial peptides (AMPs) are considered as potential substitutes of antibiotics in the field of new anti-infective drug design. There have been several machine learning algorithms and web servers in identifying AMPs and their functional activities. However, there is still room for improvement in prediction algorithms and feature extraction methods. Read More

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Voxel-Wise Feature Selection Method for CNN Binary Classification of Neuroimaging Data.

Front Neurosci 2021 20;15:630747. Epub 2021 Apr 20.

IRCCS SDN, Naples, Italy.

Voxel-wise group analysis is presented as a novel feature selection (FS) technique for a deep learning (DL) approach to brain imaging data classification. The method, based on a voxel-wise two-sample -test and denoted as -masking, is integrated into the learning procedure as a data-driven FS strategy. t-Masking has been introduced in a convolutional neural network (CNN) for the test bench of binary classification of very-mild Alzheimer's disease vs. Read More

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A Major Depressive Disorder Classification Framework based on EEG Signals using Statistical, Spectral, Wavelet, Functional Connectivity, and Nonlinear Analysis.

J Neurosci Methods 2021 May 3:109209. Epub 2021 May 3.

Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Background: Major depressive disorder (MDD) is a prevalent mental illness that is diagnosed through questionnaire-based approaches; however, these methods may not lead to an accurate diagnosis. In this regard, many studies have focused on using electroencephalogram (EEG) signals and machine learning techniques to diagnose MDD.

New Method: This paper proposes a machine learning framework for MDD diagnosis, which uses different types of EEG-derived features. Read More

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Coevolutionary dynamics of genetic traits and their long-term extended effects under non-random interactions.

J Theor Biol 2021 May 3:110750. Epub 2021 May 3.

Department of Evolutionary Studies of Biosystems, School of Advanced Sciences, SOKENDAI (The Graduate University for Advanced Studies), Shonan Village, Hayama, Kanagawa 240-0193, Japan.

Organisms continuously modify their living conditions via extended genetic effects on their environment, microbiome, and in some species culture. These effects can impact the fitness of current but also future conspecifics due to non-genetic transmission via ecological or cultural inheritance. In this case, selection on a gene with extended effects depends on the degree to which current and future genetic relatives are exposed to modified conditions. Read More

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Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data.

Lancet Psychiatry 2021 May 3. Epub 2021 May 3.

Department of Clinical Psychology, Faculty of Psychology, University of Bergen, Bergen, Norway.

Background: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom.

Methods: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. Read More

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Clinical factors associated with rapid treatment of sepsis.

PLoS One 2021 6;16(5):e0250923. Epub 2021 May 6.

Pulmonary and Critical Care Division, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States of America.

Purpose: To understand what clinical presenting features of sepsis patients are historically associated with rapid treatment involving antibiotics and fluids, as appropriate.

Design: This was a retrospective, observational cohort study using a machine-learning model with an embedded feature selection mechanism (gradient boosting machine).

Methods: For adult patients (age ≥ 18 years) who were admitted through Emergency Department (ED) meeting clinical criteria of severe sepsis from 11/2007 to 05/2018 at an urban tertiary academic medical center, we developed gradient boosting models (GBMs) using a total of 760 original and derived variables, including demographic variables, laboratory values, vital signs, infection diagnosis present on admission, and historical comorbidities. Read More

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Detecting Sensitive Mobility Features for Parkinson's Disease Stages Via Machine Learning.

Mov Disord 2021 May 6. Epub 2021 May 6.

Laboratory for Early Markers Of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel.

Background: It is not clear how specific gait measures reflect disease severity across the disease spectrum in Parkinson's disease (PD).

Objective: To identify the gait and mobility measures that are most sensitive and reflective of PD motor stages and determine the optimal sensor location in each disease stage.

Methods: Cross-sectional wearable-sensor records were collected in 332 patients with PD (Hoehn and Yahr scale I-III) and 100 age-matched healthy controls. Read More

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Cutting edge selection: learning from high reliability organisations for virtual recruitment in surgery during the COVID-19 pandemic.

Ann R Coll Surg Engl 2021 May 6. Epub 2021 May 6.

Portsmouth Hospitals University NHS Trust, UK.

Introduction: National selection for higher surgical training (ST3+) recruitment in the UK is competitive. The process must prioritise patient safety while being credible, impartial and fair. During the COVID-19 pandemic, all face-to-face interviews were cancelled. Read More

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Reinforcement learning approaches to hippocampus-dependent flexible spatial navigation.

Brain Neurosci Adv 2021 Jan-Dec;5:2398212820975634. Epub 2021 Apr 9.

School of Psychology, University of Nottingham, Nottingham, UK.

Humans and non-human animals show great flexibility in spatial navigation, including the ability to return to specific locations based on as few as one single experience. To study spatial navigation in the laboratory, watermaze tasks, in which rats have to find a hidden platform in a pool of cloudy water surrounded by spatial cues, have long been used. Analogous tasks have been developed for human participants using virtual environments. Read More

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X-architecture Steiner minimal tree algorithm based on multi-strategy optimization discrete differential evolution.

PeerJ Comput Sci 2021 13;7:e473. Epub 2021 Apr 13.

College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China.

Global routing is an important link in very large scale integration (VLSI) design. As the best model of global routing, X-architecture Steiner minimal tree (XSMT) has a good performance in wire length optimization. XSMT belongs to non-Manhattan structural model, and its construction process cannot be completed in polynomial time, so the generation of XSMT is an NP hard problem. Read More

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Optimal 1-NN prototypes for pathological geometries.

PeerJ Comput Sci 2021 9;7:e464. Epub 2021 Apr 9.

Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, Canada.

Using prototype methods to reduce the size of training datasets can drastically reduce the computational cost of classification with instance-based learning algorithms like the k-Nearest Neighbour classifier. The number and distribution of prototypes required for the classifier to match its original performance is intimately related to the geometry of the training data. As a result, it is often difficult to find the optimal prototypes for a given dataset, and heuristic algorithms are used instead. Read More

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Multi-level aspect based sentiment classification of Twitter data: using hybrid approach in deep learning.

PeerJ Comput Sci 2021 13;7:e433. Epub 2021 Apr 13.

Department of Computer Sciences, Quaid-i-Azam University, Islamabad, Pakistan.

Social media is a vital source to produce textual data, further utilized in various research fields. It has been considered an essential foundation for organizations to get valuable data to assess the users' thoughts and opinions on a specific topic. Text classification is a procedure to assign tags to predefined classes automatically based on their contents. Read More

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Weighted-Attribute Triplet Hashing for Large-Scale Similar Judicial Case Matching.

Comput Intell Neurosci 2021 16;2021:6650962. Epub 2021 Apr 16.

School of Software, Shandong University, Jinan, China.

Similar judicial case matching aims to enable an accurate selection of a judicial document that is most similar to the target document from multiple candidates. The core of similar judicial case matching is to calculate the similarity between two fact case documents. Owing to similar judicial case matching techniques, legal professionals can promptly find and judge similar cases in a candidate set. Read More

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Home Textile Pattern Emotion Labeling Using Deep Multi-View Feature Learning.

Front Psychol 2021 19;12:666074. Epub 2021 Apr 19.

Department of Medical Informatics, Nantong University, Nantong, China.

Different home textile patterns have different emotional expressions. Emotion evaluation of home textile patterns can effectively improve the retrieval performance of home textile patterns based on semantics. It can not only help designers make full use of existing designs and stimulate creative inspiration but also help users select designs and products that are more in line with their needs. Read More

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Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Nat Protoc 2021 May 5. Epub 2021 May 5.

DeepMind, London, UK.

Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-learning risk models that can predict various clinical and operational outcomes from structured electronic health record (EHR) data. The protocol comprises five main stages: formal problem definition, data pre-processing, architecture selection, calibration and uncertainty, and generalizability evaluation. Read More

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Selection of nitrogen responsive root architectural traits in spinach using machine learning and genetic correlations.

Sci Rep 2021 May 5;11(1):9536. Epub 2021 May 5.

Texas A&M AgriLife Research and Extension Center, Uvalde, TX, 78801, USA.

The efficient acquisition and transport of nutrients by plants largely depend on the root architecture. Due to the absence of complex microbial network interactions and soil heterogeneity in a restricted soilless medium, the architecture of roots is a function of genetics defined by the soilless matrix and exogenously supplied nutrients such as nitrogen (N). The knowledge of root trait combinations that offer the optimal nitrogen use efficiency (NUE) is far from being conclusive. Read More

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Tongue image quality assessment based on a deep convolutional neural network.

BMC Med Inform Decis Mak 2021 May 5;21(1):147. Epub 2021 May 5.

Basic Medical College Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai, 201203, China.

Background: Tongue diagnosis is an important research field of TCM diagnostic technology modernization. The quality of tongue images is the basis for constructing a standard dataset in the field of tongue diagnosis. To establish a standard tongue image database in the TCM industry, we need to evaluate the quality of a massive number of tongue images and add qualified images to the database. Read More

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Sentinel lymph node in cervical cancer: time to move forward.

Chin Clin Oncol 2021 Apr;10(2):18

Breast, Gynecology and Reconstructive Surgery Unit, Institut Curie, Paris, France.

In early-stage cervical cancer, lymph node status is of paramount importance to determine the best therapeutic strategy and is one of the most important prognostic factors of survival. According to main international guidelines, pelvic full lymphadenectomy is recommended for lymph node staging. Sentinel lymph node (SLN) biopsy is an accurate method for the assessment of lymph nodal involvement and has been suggested instead of systematic pelvic lymph node dissection (PLND). Read More

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MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction.

Brief Bioinform 2021 May 5. Epub 2021 May 5.

Xiangya School of Pharmaceutical Sciences, Central South University, China.

Motivation: Accurate and efficient prediction of molecular properties is one of the fundamental issues in drug design and discovery pipelines. Traditional feature engineering-based approaches require extensive expertise in the feature design and selection process. With the development of artificial intelligence (AI) technologies, data-driven methods exhibit unparalleled advantages over the feature engineering-based methods in various domains. Read More

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Optimal Donor Selection for Hematopoietic Cell Transplantation Using Bayesian Machine Learning.

JCO Clin Cancer Inform 2021 May;5:494-507

Center for International Blood and Marrow Transplant Research (CIBMTR), Medical College of Wisconsin, Milwaukee, WI.

Purpose: Donor selection practices for matched unrelated donor (MUD) hematopoietic cell transplantation (HCT) vary, and the impact of optimizing donor selection in a patient-specific way using modern machine learning (ML) models has not been studied.

Methods: We trained a Bayesian ML model in 10,318 patients who underwent MUD HCT from 1999 to 2014 to provide patient- and donor-specific predictions of clinically severe (grade 3 or 4) acute graft-versus-host disease or death by day 180. The model was validated in 3,501 patients from 2015 to 2016 with archived records of potential donors at search. Read More

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Extending Approximate Bayesian Computation with Supervised Machine Learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest.

Mol Ecol Resour 2021 May 5. Epub 2021 May 5.

CBGP, Univ Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France.

Simulation-based methods such as Approximate Bayesian Computation (ABC) are well-adapted to the analysis of complex scenarios of populations and species genetic history. In this context, supervised machine learning (SML) methods provide attractive statistical solutions to conduct efficient inferences about scenario choice and parameter estimation. The Random Forest methodology (RF) is a powerful ensemble of SML algorithms used for classification or regression problems. Read More

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Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

JMIR Mhealth Uhealth 2021 May 5;9(5):e25258. Epub 2021 May 5.

Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States.

Background: Accurate, objective pain assessment is required in the health care domain and clinical settings for appropriate pain management. Automated, objective pain detection from physiological data in patients provides valuable information to hospital staff and caregivers to better manage pain, particularly for patients who are unable to self-report. Galvanic skin response (GSR) is one of the physiologic signals that refers to the changes in sweat gland activity, which can identify features of emotional states and anxiety induced by varying pain levels. Read More

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Experimental tests of selection against heterospecific aggression as a driver of avian color pattern divergence.

J Evol Biol 2021 May 4. Epub 2021 May 4.

Department of Biology, Queen's University, Kingston, Ontario, K7L 3N6, Canada.

Signal divergence is thought to reduce the costs of co-occurrence for closely related species and may thereby be important in the generation and maintenance of new biodiversity. In birds, closely related, sympatric species are more divergent in their color patterns than those that live apart, but the selective pressures driving sympatric divergence in color pattern are not well understood. Here, we conducted field experiments on naïve birds using spectrometer-matched, painted 3D-printed models to test whether selection against heterospecific aggression might drive color pattern divergence in the genus Poecile. Read More

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Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

IEEE J Transl Eng Health Med 2021 15;9:4900511. Epub 2021 Apr 15.

WHO Collaborating Centre of eHealth, School of Public Health and Community MedicineUniversity of New South WalesSydneyNSW2052Australia.

Objective: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vital parameter analytics using affordable computer-aided diagnosis could not only reduce diagnosis costs but improve patient management and outcomes. Read More

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Learning gaps among statistical competencies for clinical and translational science learners.

J Clin Transl Sci 2020 Jun 19;5(1):e12. Epub 2020 Jun 19.

Division of Biomedical Statistics & Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

Introduction: Statistical literacy is essential in clinical and translational science (CTS). Statistical competencies have been published to guide coursework design and selection for graduate students in CTS. Here, we describe common elements of graduate curricula for CTS and identify gaps in the statistical competencies. Read More

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The impact of coronavirus 2019 on general surgery residency: A national survey of program directors.

Ann Med Surg (Lond) 2021 May 16;65:102285. Epub 2021 Apr 16.

Department of Cardiothoracic Surgery, University of Pittsburgh, 200 Lothrop St C, Pittsburgh, PA, 15213, USA.

Background: Coronavirus disease 2019 (COVID-19) has had a widespread impact on graduate medical education. This survey aims to assess how general surgery residency programs adapted to the initial wave of the COVID-19 pandemic in the United States (US).

Materials And Methods: General surgery program directors (PDs) in the US were invited to partake in a 16-question survey between April 17 and May 1, 2020. Read More

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Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models.

mSystems 2021 May 4;6(3). Epub 2021 May 4.

Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China

Common intestinal diseases such as Crohn's disease (CD), ulcerative colitis (UC), and colorectal cancer (CRC) share clinical symptoms and altered gut microbes, necessitating cross-disease comparisons and the use of multidisease models. Here, we performed meta-analyses on 13 fecal metagenome data sets of the three diseases. We identified 87 species and 65 pathway markers that were consistently changed in multiple data sets of the same diseases. Read More

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A filter approach for feature selection in classification: application to automatic atrial fibrillation detection in electrocardiogram recordings.

BMC Med Inform Decis Mak 2021 May 4;21(Suppl 4):130. Epub 2021 May 4.

APHM, INSERM, IRD, Sciences Economiques & Sociales de la Sante & Traitement de l'Information Médicale (SESSTIM), Hop Timone, Biostatistique et Technologies de l'Information et de la Communication (BioSTIC), Aix Marseille Univ, Marseille, France.

Background: In high-dimensional data analysis, the complexity of predictive models can be reduced by selecting the most relevant features, which is crucial to reduce data noise and increase model accuracy and interpretability. Thus, in the field of clinical decision making, only the most relevant features from a set of medical descriptors should be considered when determining whether a patient is healthy or not. This statistical approach known as feature selection can be performed through regression or classification, in a supervised or unsupervised manner. Read More

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