Article
Mathematics, Interdisciplinary Applications
Jun Wei, Tao Ye, Zhe Zhang
Summary: This study comprehensively investigates the predictability of multidimensional features on commercial bank performance using a boosting regression tree. By using an adaptively reduced step size, the model improves accuracy and generalization ability, providing better classification results compared to existing algorithms.
Article
Agronomy
Ting Zhang, Yanbo Huang, Krishna N. Reddy, Pingting Yang, Xiaohu Zhao, Jingcheng Zhang
Summary: The study utilized hyperspectral imaging to evaluate crop damage from glyphosate on non-GR corn plants and their recoverability. Spectral characteristics and sensitive bands were used to create spectral indices for crop classification. Machine learning algorithms combined with feature spectral bands showed reasonable accuracy in predicting glyphosate spray rates and differentiating between recoverable and unrecoverable corn plants. The potential of hyperspectral imaging for practical weed management in crop fields was demonstrated through various data analysis and modeling approaches.
Article
Engineering, Environmental
S. Pavithra, T. Veeramani, S. Sree Subha, P. J. Sathish Kumar, S. Shanmugan, Ammar H. Elsheikh, F. A. Essa
Summary: In this study, a sincere effort has been made to engineer a perched cum off-centered wick solar still (PCWSS). Artificial neural networks (ANNs) and optimization techniques were used to predict the efficiency and distillate yield of the system. The experimental results show that the system exhibits good prediction accuracy and productivity.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2022)
Article
Education, Scientific Disciplines
Srilakshmi Atthota, Alexa Griffiths, Aaron Kangas-Dick, Jonathan Jesneck, Ruchi Thanawala, Richard Savel, Rebecca Rhee
Summary: The implementation of a team-based Attending Meritocracy program effectively increased completion rates and quality of resident feedback, leading to more engagement and competitiveness among teaching faculty. This study explores the effectiveness of improving resident feedback, with significant positive outcomes.
JOURNAL OF SURGICAL EDUCATION
(2021)
Article
Mathematics, Applied
Ting-Hsuan Chen, Rong-Cih Chang
Summary: This study used machine learning algorithms to analyze the impact of FinTech patents on financial industry performance from 2008 to 2016. The results showed that FinTech patents can improve the profitability of the financial industry, with the influence of return on assets being more significant than that of return on equity.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Article
Agriculture, Dairy & Animal Science
Leonardo Augusto Coelho Ribeiro, Tiago Bresolin, Guilherme Jordao de Magalhaes Rosa, Daniel Rume Casagrande, Marina de Arruda Camargo Danes, Joao Ricardo Reboucas Dorea
Summary: The study evaluated the impact of different cross-validation strategies on predicting grazing activities in cattle using wearable sensor data and machine learning algorithms. The results showed that the holdout method yielded the highest accuracy values for all three machine learning approaches, while LODO and LOAO strategies performed poorly.
JOURNAL OF ANIMAL SCIENCE
(2021)
Article
Geosciences, Multidisciplinary
Ratiranjan Jena, Biswajeet Pradhan, Shilpa Gite, Abdullah Alamri, Hyuck-Jin Park
Summary: This study applied SHAP to estimate earthquake probability using two different ML approaches (ANN and RF) and compared their performance. The results showed that SHAP could help interpret the models' outputs and identify the contributing factors for earthquake probability estimation. Testing on the Indian subcontinent demonstrated high overall accuracy of the ANN and RF models.
Article
Chemistry, Physical
Joyjit Chattoraj, Brahim Hamadicharef, Yusuf Nizar Aris Syadzali, Gerren Owen Limantara, Yingzhi Zeng, Chee Kok Poh, Luwei Chen, Teck Leong Tan
Summary: This article reports the construction of a database on water-gas shift reaction using noble metal catalysts for fuel cell applications, and evaluates the effects of catalytic compositions and reaction conditions on carbon monoxide conversion using a machine learning approach with Shapley feature importance methodology. The proposed theory-guided machine learning model outperforms other state-of-the-art models and offers promising possibilities for finding suitable catalysts.
Article
Acoustics
A. Jared Miller, Scott D. Sommerfeldt, Jonathan D. Blotter
Summary: This research focuses on using machine learning models to evaluate the audio fidelity of heavy equipment acoustic simulations. By studying and comparing two datasets, a model is developed that accurately predicts human perception with high accuracy.
Article
Education & Educational Research
Bo Kim, Aishwarya Rajagopalan, Edward M. Tabasky, Sparsha S. Reddy, David R. Topor
Summary: This study developed and implemented a joint resident-faculty feedback workshop to enhance participants' understanding of challenges in the feedback process. The results showed that both faculty and residents were able to increase perspective taking about how the other group perceived the feedback process.
BMC MEDICAL EDUCATION
(2022)
Article
Computer Science, Information Systems
Julio Alberto Lopez-Gomez, Francisco P. Romero, Eusebio Angulo
Summary: This paper provides objective evaluation criteria and features for handball goalkeepers based on their actions during a match, and validates the effectiveness of these criteria and features through computer experiments and case studies.
Article
Computer Science, Artificial Intelligence
Guilherme Palumbo, Davide Carneiro, Miguel Guimares, Victor Alves, Paulo Novais
Summary: In recent years, there has been a significant increase in the number of machine learning algorithms and their parameters. This presents both opportunities and challenges in training models. Traditional search-based methods become computationally expensive and time-consuming as datasets grow, especially in data streaming scenarios. This paper proposes a meta-learning approach that can predict performance indicators and recommend the best algorithm/configuration for training models. The proposed approach is up to 130 times faster than a state-of-the-art method and only slightly worse in terms of model quality, making it suitable for scenarios that require regular model updates with shorter training time.
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
(2023)
Review
Chemistry, Physical
Xinhua Liu, Lisheng Zhang, Hanqing Yu, Jianan Wang, Junfu Li, Kai Yang, Yunlong Zhao, Huizhi Wang, Billy Wu, Nigel P. Brandon, Shichun Yang
Summary: This study demonstrates a method to evaluate the overall lifecycle of lithium-ion batteries (LIBs) and discusses the bridging role of characterization techniques and modeling. Key parameters extracted from characterization can be used as digital inputs for modeling. Furthermore, advanced computational techniques can enhance the understanding and control of the battery lifecycle. The introduction of digital twins techniques enables real-time monitoring and control, as well as intelligent manufacturing.
ADVANCED ENERGY MATERIALS
(2022)
Article
Construction & Building Technology
Mehrdad Ehsani, Pouria Hajikarimi, Masoud Esfandiar, Mohammad Rahi, Behzad Rasouli, Yousef Yousefi, Fereidoon Moghadas Nejad
Summary: This study develops deterministic and probabilistic prediction models for the multiple stress creep and recovery (MSCR) test. Crumb rubber, polyphosphoric acid, and styrene-butadiene-styrene bitumen modifiers are used to modify the high-temperature performance of base bitumens. Deterministic models are developed for each modifier individually, while a comprehensive probabilistic model is developed to predict different traffic levels. The accuracy of the probabilistic model is 0.85, and the sensitivity analysis shows the impact of modifier dosage and temperature on traffic levels.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Geochemistry & Geophysics
David R. Hanson, Heather E. Lawson
Summary: Recent NIOSH research has identified geochemical markers that correlate with in situ reportable dynamic event occurrence in the underground coal mining industry. In this study, machine learning analysis was conducted to assess the probability of dynamic failure occurrence based on geochemical and petrographic data. The analyses showed that certain geochemical parameters had a significant impact on the model performance and achieved high precision values in classification.
Article
Anesthesiology
Ephy R. Love, Franklin Dexter, Jason Reminick, Joseph A. Sanford, Suzanne Karan
Summary: The study demonstrates that applicants from the same state as the residency program may have fewer total interviews while maintaining the same odds of matching. The effect of same-state locality is a significant predictor of residency matching, while belonging to an affiliated medical school does not significantly impact the matching process.
ANESTHESIA AND ANALGESIA
(2021)
Article
Anesthesiology
Susan M. Martinelli, Fei Chen, Robert S. Isaak, Julie L. Huffmyer, Sara E. Neves, John D. Mitchell
Summary: The COVID-19 pandemic has led to changes in anesthesiology education, with the adoption of learning management systems and the flipped classroom approach. Simulation training has been crucial in preparing for caring for COVID-19 patients. Collaboration to implement best practices has the potential to improve education for all learners.
ANESTHESIA AND ANALGESIA
(2021)
Article
Surgery
Denys Shay, Pauline Y. Ng, David M. Dudzinski, Stephanie D. Grabitz, John D. Mitchell, Xinling Xu, Timothy T. Houle, Deepak L. Bhatt, Matthias Eikermann
Summary: The study aimed to identify undertreated subgroups of heart failure patients who would benefit from better perioperative optimization. Patients with heart failure have increased risks of postoperative cardiac complications after noncardiac surgery. In this analysis of hospital registry data, it was found that heart failure patients had significantly higher risks of cardiac complications. Clinicians often make insufficient attempts to optimize the clinical condition of lower-risk heart failure patients preoperatively, but appropriate preoperative preventive treatment can significantly reduce their risk of postoperative cardiac complications.
Article
Anesthesiology
Huma Fatima, Feroze Mahmood, Syed Hamza Mufarrih, John D. Mitchell, Vanessa Wong, Rabia Amir, Ting Hai, Mario Montealegre, Stephanie B. Jones, Ziyad O. Knio, Robina Matyal
Summary: This study describes a formal, structured program for perioperative ultrasound training which effectively trained first-year clinical anesthesia residents. The training program improved residents' cognitive knowledge test scores and helped them achieve a proficiency index comparable to graduating residents who underwent traditional ultrasound training.
ANESTHESIA AND ANALGESIA
(2022)
Article
Anesthesiology
Aditee P. Ambardekar, K. Karisa Walker, Anne Marie McKenzie-Brown, Kaitlyn Brennan, Chelsia Jackson, Laura Edgar, Herodotos Ellinas, Timothy R. Long, Carlos E. Trombetta, Martin G. Laskey, Bradley W. Wargo, Rupa J. Dainer, Crys S. Draconi, John D. Mitchell
Summary: The shift from time-based to competency-based medical education began nearly 30 years ago and is slowly taking shape, with the development of valid assessment tools being the first step. The ACGME is committed to ensuring that residency programs produce competent, safe, and compassionate doctors. The Milestones Project is the current strategy in evolving to a competency-based system, with ongoing efforts to address challenges and improve assessment and faculty development tools.
ANESTHESIA AND ANALGESIA
(2021)
Article
Anesthesiology
Vincent Baribeau, Jeffrey Weinstein, Vanessa T. Wong, Aidan Sharkey, Derek N. Lodico, Robina Matyal, Feroze Mahmood, John D. Mitchell
Summary: Graduate medical education is largely based on a time-based apprenticeship model, and motion tracking technology can provide a more detailed assessment of student skill performance, ultimately improving educational standards and efficiency.
JOURNAL OF CARDIOTHORACIC AND VASCULAR ANESTHESIA
(2022)
Article
Medicine, General & Internal
Alex Hincker, Jacob Nadler, Suzanne Karan, Ebony Carter, Shay Porat, Barbara Warner, Yo-El S. Ju, Arbi Ben Abdallah, Elizabeth Wilson, Ellen M. Lockhart, Yehuda Ginosar
Summary: This study aims to investigate the relationship between maternal obstructive sleep apnoea (OSA) and fetal growth restriction (FGR), hypothesizing that treating OSA patients with positive airway pressure (PAP) can improve birth weight and neonatal outcomes.
Article
Orthopedics
Catherine E. Hutchison, Jason I. Reminick, Ephy R. Love, Suzanne Karan, Kenneth R. Gundle
Summary: During the 2020 to 2021 residency application cycle, less than half of orthopaedic residency programs strictly adhered to the guidelines of the universal interview offer day (UIOD). The average time to fill 80% capacity for the 33 programs that released on the UIOD was 26 minutes. Applicants with edu email domains scheduled their first interview an average of 1.8 minutes later than those with com email domains.
JOURNAL OF THE AMERICAN ACADEMY OF ORTHOPAEDIC SURGEONS
(2022)
Letter
Education, Scientific Disciplines
Dustin C. Lin, Vincent Baribeau, Jonathan J. Wisco, John D. Mitchell
MEDICAL SCIENCE EDUCATOR
(2022)
Article
Medicine, General & Internal
Ephy R. Love, Franklin Dexter, Jason I. Reminick, Suzanne B. Karan
Summary: This study demonstrates that anesthesiology residency programs can substantially reduce the number of interviews conducted without significantly affecting their rank-to-match lists, allowing program leadership to make more informed decisions when selecting interviewees.
CUREUS JOURNAL OF MEDICAL SCIENCE
(2021)
Article
Medicine, General & Internal
Courtney Vidovich, Andres Laserna, Suzanne B. Karan
Summary: Robotic-assisted radical prostatectomy has become increasingly popular in the last two decades, but carries a risk of venous air embolism. This report describes a rare clinical case of VAE during RARP, which was successfully managed by adjusting surgical techniques and oxygen supply.
CUREUS JOURNAL OF MEDICAL SCIENCE
(2021)
Article
Medicine, General & Internal
Gregory A. Kirby, Wenjuan Guo, John D. Mitchell, Haobo Ma
Summary: Neuraxial anesthesia is safe and effective for elderly patients undergoing hip or knee surgery, but it can be challenging to establish in this group due to anatomical abnormalities. The modified Taylor's approach, based on preoperative lumbar x-ray interpretation, can successfully perform spinal anesthesia in elderly patients with anatomical difficulties.
CUREUS JOURNAL OF MEDICAL SCIENCE
(2021)
Article
Anesthesiology
Daniel P. Walsh, Sara E. Neves, Vanessa T. Wong, John D. Mitchell