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Pablo Caballero, Luis Gonzalez-Abril, Juan A. Ortega and Áurea Simon-Soro
Endometriosis (EM) is a chronic inflammatory estrogen-dependent disorder that affects 10% of women worldwide. It affects the female reproductive tract and its resident microbiota, as well as distal body sites that can serve as surrogate markers of EM. Cu...
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Pannapa Changpetch, Apasiri Pitpeng, Sasiprapa Hiriote and Chumpol Yuangyai
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Padmavathi Janardhanan,Heena L.,Fathima Sabika
Pág. 25 - 30
The idea of medical data mining is to extract hidden knowledge in medical field using data mining techniques. One of the positive aspects is to discover the important patterns. It is possible to identify patterns even if we do not have fully understood t...
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Kanza Gulzar, Muhammad Ayoob Memon, Syed Muhammad Mohsin, Sheraz Aslam, Syed Muhammad Abrar Akber and Muhammad Asghar Nadeem
In the public health sector and the field of medicine, the popularity of data mining and its usage in knowledge discovery and databases (KDD) are rising. The growing popularity of data mining has discovered innovative healthcare links to support decision...
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László Beinrohr, Eszter Kail, Péter Piros, Erzsébet Tóth, Rita Fleiner and Krasimir Kolev
Data science and machine learning are buzzwords of the early 21st century. Now pervasive through human civilization, how do these concepts translate to use by researchers and clinicians in the life-science and medical field? Here, we describe a software ...
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Jiyang Wang, Chen Wang and Wenyu Zhang
In recent years, healthcare has attracted much attention, which is looking for more and more data analytics in healthcare to relieve medical problems in medical staff shortage, ageing population, people living alone, and quality of life. Data mining, ana...
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Ioannis E. Livieris, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas
During the last decades, intensive efforts have been devoted to the extraction of useful knowledge from large volumes of medical data employing advanced machine learning and data mining techniques. Advances in digital chest radiography have enabled resea...
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Baocheng Wang and Zetao Li
Recently, with the great development of e-health, more and more countries have made certain achievements in the field of electronic medical treatment. The digitization of medical equipment and the structuralization of electronic medical records are the g...
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Oguz Akbilgic, Ramin Homayouni, Kevin Heinrich, Max Raymond Langham and Robert Lowell Davis
Text fields in electronic medical records (EMR) contain information on important factors that influence health outcomes, however, they are underutilized in clinical decision making due to their unstructured nature. We analyzed 6497 inpatient surgical cas...
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Umesh Kokate, Arvind Deshpande, Parikshit Mahalle and Pramod Patil
Data growth in today?s world is exponential, many applications generate huge amount of data streams at very high speed such as smart grids, sensor networks, video surveillance, financial systems, medical science data, web click streams, network data, etc...
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Gopi Battineni, Nalini Chintalapudi and Gregory Zacharewicz
An acknowledgment of feedback is extremely helpful in medical training, as it may improve student skill development and provide accurate, unbiased feedback. Data are generated by hundreds of complicated and variable processes within healthcare including ...
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Yufri Isnaini Rochmat Maulana, Tessy Badriyah, Iwan Syarif
Pág. 151 - 167
Diabetes is a very serious chronic. Diabetes can occurs when the pancreas doesn't produce enough insulin (a hormone used to regulate blood sugar), cause glucose in the blood to be high. The purpose of this study is to provide a different approach in deal...
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Vangelis Sarlis, George Papageorgiou and Christos Tjortjis
Injuries are an unfortunate part of professional sports. This study aims to explore the multi-dimensional impact of injuries in professional basketball, focusing on player performance, team dynamics, and economic outcomes. Employing advanced machine lear...
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Panagiotis Pintelas and Ioannis E. Livieris
During the last decades, in the area of machine learning and data mining, the development of ensemble methods has gained a significant attention from the scientific community. Machine learning ensemble methods combine multiple learning algorithms to obta...
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Ulises Manuel Ramirez-Alcocer, Edgar Tello-Leal, Gerardo Romero and Bárbara A. Macías-Hernández
In this paper, we propose a deep learning-based approach to predict the next event in hospital organizational process models following the guidance of predictive process mining. This method provides value for the planning and allocating of resources sinc...
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Aditya Singhal and Vijay Mago
The use of Twitter by healthcare organizations is an effective means of disseminating medical information to the public. However, the content of tweets can be influenced by various factors, such as health emergencies and medical breakthroughs. In this st...
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Negar Orangi-Fard, Alireza Akhbardeh and Hersh Sagreiya
Predicting ICU readmission risk will help physicians make decisions regarding discharge. We used discharge summaries to predict ICU 30-day readmission risk using text mining and machine learning (ML) with data from the Medical Information Mart for Intens...
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Angela Shin-Yu Lien, Yi-Der Jiang, Jia-Ling Tsai, Jawl-Shan Hwang and Wei-Chao Lin
Fatigue and poor sleep quality are the most common clinical complaints of people with diabetes mellitus (DM). These complaints are early signs of DM and are closely related to diabetic control and the presence of complications, which lead to a decline in...
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