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Seaborn: Statistical Data Visualization

Journal of Open Source Software, 2021
seaborn is a library for making statistical graphics in Python. It provides a high-level interface to matplotlib and integrates closely with pandas data structures. Functions in the seaborn library expose a declarative, dataset-oriented API that makes it
Michael L. Waskom
semanticscholar   +1 more source

Validation of the Patient Health Questionnaire-9 (PHQ-9) in human medicine interns at a reference university in Peru during the COVID-19 pandemic

Revista de la Facultad de Medicina Humana, 2022
Objectives: Validate a questionnaire to establish the perception of difficulties in the development of research projects in the students of the research area of ​​the Faculty of Human Medicine of the Peruvian University Los Andes.
Efraín A. Cehua Alvarez, Horus Virú-Flores, Joseph Alburqueque-Melgarejo, Juan C. Roque-Quezada, Jamee Guerra Valencia, Geremi A. Gonzales Matta, Magdiel José M. Gonzales Menéndez, David A. Laván Quiroz   +7 more
doaj   +1 more source

Statistical analysis of vegetable productivity dynamics of Uzbekistan [PDF]

BIO Web of Conferences, 2023
In all fields, there are a lot of random events at a given time. In particular, the process of growing agricultural crops, which is repeated over a certain period, that is, seasonally, is the basis for our analysis as a discrete {Yt,t ∈ T} random dynamic
Fayziev Akhtamjon, Ruzmetov Kudrat, Noraliev Nurilla, Turgunov Tolibjon   +3 more
doaj   +1 more source

Clustering CITE-seq data with a canonical correlation-based deep learning method

Frontiers in Genetics, 2022
Single-cell multiomics sequencing techniques have rapidly developed in the past few years. Among these techniques, single-cell cellular indexing of transcriptomes and epitopes (CITE-seq) allows simultaneous quantification of gene expression and surface ...
Musu Yuan, Liang Chen, Minghua Deng, Minghua Deng, Minghua Deng   +4 more
doaj   +1 more source

An introduction to statistical learning with applications in R

Statistical Theory and Related Fields, 2021
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Fariha Sohil, Muhammad Umair Sohali, J. Shabbir   +2 more
semanticscholar   +1 more source

Psychosis Relapse Prediction Leveraging Electronic Health Records Data and Natural Language Processing Enrichment Methods

Frontiers in Psychiatry, 2022
BackgroundIdentifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited.
Dong Yun Lee, Chungsoo Kim, Seongwon Lee, Seongwon Lee, Sang Joon Son, Sun-Mi Cho, Yong Hyuk Cho, Jaegyun Lim, Rae Woong Park, Rae Woong Park   +9 more
doaj   +1 more source

Development and Validation of Smoking Abstinence Self-efficacy Scale among Iranian Female Adolescents [PDF]

Journal of Evidence-Based Care, 2020
Background: Among different factors, self-efficacy is one of the most suitable components for predicting smoking behavior among adolescents. Therefore, it is essential to design a native tool to measure this high-risk behavior in adolescents and ...
Zienab Rafiee, Fatemeh Heshmati Nabavi, Hamid Heidarian Miri, Abdolghader Assarroudi   +3 more
doaj   +1 more source

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation [PDF]

Conference on Empirical Methods in Natural Language Processing, 2014
In this paper, we propose a novel neural network model called RNN Encoder‐ Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixedlength vector representation, and the other decodes the ...
Kyunghyun Cho, B. V. Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio   +6 more
semanticscholar   +1 more source

Ten Epidemiological Parameters of COVID-19: Use of Rapid Literature Review to Inform Predictive Models During the Pandemic

Frontiers in Public Health, 2020
Objective: To describe the methods used in a rapid review of the literature and to present the main epidemiological parameters that describe the transmission of SARS-Cov-2 and the illness caused by this virus, coronavirus disease 2019 (COVID-19).Methods:
Luciana Guerra Gallo, Ana Flávia de Morais Oliveira, Ana Flávia de Morais Oliveira, Amanda Amaral Abrahão, Leticia Assad Maia Sandoval, Yure Rodrigues Araújo Martins, Maria Almirón, Fabiana Sherine Ganem dos Santos, Wildo Navegantes Araújo, Wildo Navegantes Araújo, Maria Regina Fernandes de Oliveira, Maria Regina Fernandes de Oliveira, Henry Maia Peixoto, Henry Maia Peixoto   +13 more
doaj   +1 more source

On direct sequential analysis of heart rate variability signals [PDF]

Archive of Oncology, 2005
Heart rate variability analysis represents one of the most promising and the most commonly used quantitative measures of the cardiovascular autonomic regulatory system.
Bajić Dragana, Lončar-Turukalo Tatjana, Šibarević Olijandra   +2 more
doaj   +1 more source