Article
Computer Science, Information Systems
N. Divyashree, Nandini K. S. Prasad
Summary: The strength of predictive analytics lies in uncovering and aiding decision-making processes by revealing interesting patterns that may be obscured. This research proposes the implementation of predictive analytics using a multi-stratified algorithm called LWGMK-NN, which does not rely on preset assumptions, to discover insights and make predictions. Experimental results using various performance metrics validate the efficiency of the LWGMK-NN algorithm as a predictive model.
Article
Chemistry, Multidisciplinary
Komal Naz, Isma Farah Siddiqui, Jahwan Koo, Mohammad Ali Khan, Nawab Muhammad Faseeh Qureshi
Summary: Employee churn analytics is a process that assesses and predicts employee turnover rate in a company, aiming to reduce churn issue and additional costs. This paper proposes an IoT-enabled predictive strategy to identify future churners through analyzing features and performing classification, achieving a high accuracy rate in the experiment.
APPLIED SCIENCES-BASEL
(2022)
Article
Multidisciplinary Sciences
Maulin Raval, Pavithra Sivashanmugam, Vu Pham, Hardik Gohel, Ajeet Kaushik, Yun Wan
Summary: Accurate rainfall prediction is crucial for policy making and sustainable resource management. Australia is facing challenges of drought, and machine learning algorithms are playing a role in rainfall prediction.
SCIENTIFIC REPORTS
(2021)
Article
Medicine, General & Internal
Zhuoxin Yang, Ji Xuan, Fengwu Yang, Ying Qi, Miaofang Yang, Huabing Xu, Mingzuo Jiang, Si Shen, Mengjie Lu, Hui Shi, Kang Jiang, Hui Tao, Yuxiu Liu, Fangyu Wang
Summary: This study aims to determine the superiority of urgent endoscopy over non-urgent endoscopy in reducing the rebleeding rate of patients with cirrhosis who experience acute variceal haemorrhage (AVH). The study is a single-centred, prospective, randomised clinical trial with an estimated 400 participants. The results of this study could provide valuable evidence to guide clinical research and treatment.
Article
Business
Behrooz Davazdahemami, Pankush Kalgotra, Hamed M. Zolbanin, Dursun Delen
Summary: This study proposes a developer-oriented recommender model that uses network analytics, deep learning-based natural language processing, and explainable artificial intelligence techniques to predict potential recommendation relationships among apps. The model helps app developers target appropriate consumers and increase the chances of success for their apps.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Weike Sun, Richard D. Braatz
Summary: Data analytics tools are transforming decision-making and design processes in manufacturing, but selecting the best method requires expertise. The Smart Process Analytics framework allows users to focus on goals rather than methods, effectively transforming manufacturing data into intelligent information through domain knowledge, data characteristics, and method selection through cross-validation.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Rheumatology
Kai Zhang, Yuan An, Peng Zhao, Bo Huang, Yifan Wang, Xingyu Zhou, Gong Cheng, Xiaoyan Xing, Naidi Wang, Ruiling Feng, Siyue Yu, Min Li, Jing He, Zhanguo Li
Summary: This study aimed to identify predictors for achieving and maintaining lupus low disease activity state (LLDAS), as well as predictors for early achievement of LLDAS and long-term disease activity. Renal involvement, haematological involvement, and hypocomplementaemia were found to be negative predictors for LLDAS achievement and maintenance. LLDAS-3mo was a positive predictor for long-term sustainment of LLDAS. A prognostic stratification tool for LLDAS was established based on the identified risk factors.
Article
Management
Laurens Deprez, Katrien Antonio, Robert Boute
Summary: With manufacturers shifting focus, full-service maintenance contracts are gaining popularity, requiring considerations for the diversity in machine configurations. Pricing strategy should be differentiated based on expected costs and machine characteristics to prevent adverse selection from impacting profitability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Review
Oncology
Gian Franco Zannoni, Emma Bragantini, Francesca Castiglione, Matteo Fassan, Giancarlo Troncone, Frediano Inzani, Anna Pesci, Angela Santoro, Filippo Fraggetta
Summary: This review discusses the importance of a new histomolecular classification system for endometrial carcinoma (EC) in clinical practice and presents the most commonly adopted immunohistochemical and molecular biomarkers for characterizing EC in daily clinical settings.
FRONTIERS IN ONCOLOGY
(2022)
Article
Multidisciplinary Sciences
Magdalyn E. Elkin, Xingquan Zhu
Summary: By using machine learning to analyze terminated clinical trials, the study identified common factors associated with trial termination and accurately predicted trial termination. The results demonstrate that machine learning has high predictive accuracy in clinical trial studies.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Artificial Intelligence
Emanuele Di Fiore, Antonino Ferraro, Antonio Galli, Vincenzo Moscato, Giancarlo Sperli
Summary: The paper proposes a novel deep learning-based methodology for anomalous sound detection, which is characterized by flexibility, modularity, and efficiency. The methodology calculates an anomaly score by jointly analyzing audio features and machine identifier information, and its efficiency and effectiveness are demonstrated through multiple experiments.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematical & Computational Biology
Tingyang Ren, Weining Shen, Liwen Zhang, Haibing Zhao
Summary: In this study, a Bayesian approach was proposed to monitor noncompliance in clinical trials, using principal stratification framework and Bayesian additive regression trees. The design showed excellent performance in simulation studies when dealing with noncompliance issues.
STATISTICS IN MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Matthias Bogaert, Michel Ballings, Dirk Van den Poel, Asil Oztekin
Summary: The research shows that social media data significantly increases the predictive power of traditional box office prediction models. Facebook data outperforms Twitter data and including user-generated content consistently improves predictive power. Combination variables based on volume and valence of Facebook comments are identified as the most important variables.
DECISION SUPPORT SYSTEMS
(2021)
Article
Management
Marshall Fisher, Santiago Gallino, Serguei Netessine
Summary: This study introduces a new method for determining retail store associate staffing levels at the individual store level, demonstrating its effectiveness through historical data and field testing. The impact of staffing levels on revenue was found to vary greatly by store. By implementing this method, retailers can increase revenue and profitability through better labor management.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Serhat Simsek, Abdullah Albizri, Marina Johnsosn, Tyler Custis, Stephan Weikert
Summary: Predictive analytics and artificial intelligence are crucial for improving organizational performance and managerial decision-making. This study focused on identifying MLB free agents likely to receive a contract, using a design science research paradigm and CAM theory to develop a framework. The research found that a player's statistical performance and factors like age, Wins above Replacement, and last team played for are significant in predicting contract signings.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2021)
Review
Clinical Neurology
Neta Zach, David L. Ennist, Albert A. Taylor, Hagit Alon, Alexander Sherman, Robert Kueffner, Jason Walker, Ervin Sinani, Igor Katsovskiy, Merit Cudkowicz, Melanie L. Leitner
Article
Clinical Neurology
Albert A. Taylor, Christina Fournier, Meraida Polak, Liuxia Wang, Neta Zach, Mike Keymer, Jonathan D. Glass, David L. Ennist
ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY
(2016)
Article
Clinical Neurology
Samad Jahandideh, Albert A. Taylor, Danielle Beaulieu, Mike Keymer, Lisa Meng, Amy Bian, Nazem Atassi, Jinsy Andrews, David L. Ennist
AMYOTROPHIC LATERAL SCLEROSIS AND FRONTOTEMPORAL DEGENERATION
(2018)
Article
Clinical Neurology
Katharine Nicholson, James Chan, Eric A. Macklin, Mark Levine-Weinberg, Christopher Breen, Rachit Bakshi, Daniela L. Grasso, Anne-Marie Wills, Samad Jahandideh, Albert A. Taylor, Danielle Beaulieu, David L. Ennist, Ovidiu Andronesi, Eva-Maria Ratai, Michael A. Schwarzschild, Merit Cudkowicz, Sabrina Paganoni
ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY
(2018)
Article
Medicine, Research & Experimental
David Alan Schoenfeld, Dianne M. Finkelstein, Eric Macklin, Neta Zach, David L. Ennist, Albert A. Taylor, Nazem Atassi
Article
Clinical Neurology
Benjamin Rix Brooks, Erik P. Pioro, Danielle Beaulieu, Albert A. Taylor, Mark Schactman, Mike Keymer, Wendy Agnese, Johnna Perdrizet, Stephen Apple, David L. Ennist
Summary: This study utilized a machine learning model for predictions and a novel method for subgroup identification, confirming a significant treatment effect of edaravone on participants with broader disease characteristics.
AMYOTROPHIC LATERAL SCLEROSIS AND FRONTOTEMPORAL DEGENERATION
(2022)
Article
Clinical Neurology
Danielle Beaulieu, James D. Berry, Sabrina Paganoni, Jonathan D. Glass, Christina Fournier, Jonavelle Cuerdo, Mark Schactman, David L. Ennist
Summary: Introduction: The study developed a machine-learning survival model without using baseline VC, showing strong discrimination for stratifying ALS patients and effectively excluding those with lower survival probabilities.
AMYOTROPHIC LATERAL SCLEROSIS AND FRONTOTEMPORAL DEGENERATION
(2021)
Article
Virology
MZ Zhu, JA Bristol, YF Xie, M Mina, H Ji, S Forry-Schaudies, DL Ennist
JOURNAL OF VIROLOGY
(2005)
Article
Biotechnology & Applied Microbiology
KD Burroughs, DB Kayda, K Sakhuja, Y Hudson, J Jakubczak, JA Bristol, D Ennist, P Hallenbeck, M Kaleko, S Connelly
CANCER GENE THERAPY
(2004)
Article
Biotechnology & Applied Microbiology
JA Bristol, MZ Zhu, H Ji, M Mina, YF Xie, L Clarke, S Forry-Schaudies, DL Ennist
Article
Oncology
N Ramesh, Y Ge, DL Ennist, MZ Zhu, M Mina, S Ganesh, PS Reddy, DC Yu
CLINICAL CANCER RESEARCH
(2006)