Article
Urology & Nephrology
Agathe Truchot, Marc Raynaud, Nassim Kamar, Maarten Naesens, Christophe Legendre, Michel Delahousse, Olivier Thaunat, Matthias Buchler, Marta Crespo, Kamilla Linhares, Babak J. Orandi, Enver Akalin, Gervacio Soler Pujol, Helio Tedesco Silva, Gaurav Gupta, Dorry L. Segev, Xavier Jouven, Andrew J. Bentall, Mark D. Stegall, Carmen Lefaucheur, Olivier Aubert, Alexandre Loupy
Summary: In this study, machine learning models were developed and compared to traditional approaches for predicting kidney allograft outcomes. Despite good overall performances, the machine learning models did not outperform the traditional Cox-Based Prognostication System in predicting kidney allograft failure. Therefore, the study supports the continued use of traditional statistical approaches for kidney graft prognostication.
KIDNEY INTERNATIONAL
(2022)
Article
Psychology, Multidisciplinary
Muhammad Usman Tariq, Muhammad Babar, Marc Poulin, Akmal Saeed Khattak, Mohammad Dahman Alshehri, Sarah Kaleem
Summary: The article discusses the evolution of intelligent big data analysis in the age of big data and artificial intelligence, focusing on the challenges of analyzing human behavior through social media data. It proposes an architecture to efficiently process massive social media datasets and demonstrates its effectiveness using data from Dailymotion.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Orthopedics
Siyuan Zhang, Bernard Puang Huh Lau, Yau Hong Ng, Xinyu Wang, Weiliang Chua
Summary: This study compared the predictive performance of machine learning algorithms and preoperative PROM thresholds in predicting minimal clinically important difference (MCID) attainment at 2 years after total knee arthroplasty (TKA). Both methods performed similarly, with the patient's preoperative PROM score being the most important predictor of MCID attainment. ROC analysis identified optimal preoperative threshold values for the SF-36 PCS, MCS, and WOMAC, providing insight for future research.
KNEE SURGERY SPORTS TRAUMATOLOGY ARTHROSCOPY
(2022)
Article
Chemistry, Multidisciplinary
Tamas Orosz, Renato Vagi, Gergely Mark Csanyi, Daniel Nagy, Istvan Uveges, Janos Pal Vadasz, Andrea Megyeri
Summary: In recent years, many machine learning-based document processing applications have been developed, which can reduce costs and reshape company structures. These applications can replace trainees, allowing experts to focus on higher-value tasks and foster innovation. However, the development cost of these methods is often high and not straightforward. This paper presents a survey that compares a machine learning-based legal text labeler with individuals possessing legal domain knowledge. The results show the effectiveness and accuracy of the machine learning system and highlight the potential for increased discoverability and value enrichment.
APPLIED SCIENCES-BASEL
(2022)
Article
Multidisciplinary Sciences
Arturo Moncada-Torres, Marissa C. van Maaren, Mathijs P. Hendriks, Sabine Siesling, Gijs Geleijnse
Summary: This study compares the performance of Cox Proportional Hazards (CPH) analysis and machine learning techniques in predicting survival rates for non-metastatic breast cancer patients. The results show that machine learning models can outperform classical methods, with Extreme Gradient Boosting (XGB) performing even better. By utilizing Shapley Additive Explanation (SHAP) values, the study explains the predictions of the models, demonstrating the importance of explainable machine learning in healthcare.
SCIENTIFIC REPORTS
(2021)
Review
Construction & Building Technology
Joanna Kolata, Piotr Zierke
Summary: Architects need to have a wide range of knowledge and creativity, but recent advancements in information technology have brought significant changes to the profession. This review article examines the impact of computer technologies on architectural design work and raises questions about the possibility of computer algorithms replacing architects.
Article
Computer Science, Information Systems
Anil Pise, Byungun Yoon, Saurabh Singh
Summary: In recent years, there has been significant research in healthcare and administration of cutting-edge ambient intelligence (AmI) technology. Healthcare experts have explored smart gadgets, medical technologies, and ambient intelligence using Internet of Things (IoT) (AIoT). The potential to improve care for individuals living in rural and distant areas by linking these two fields is evident. The healthcare industry has experienced tremendous advances in efficiency, affordability, and usefulness, thanks to new growth opportunities and significant cost reductions. The application of AIoT-H is expected to be covered in the last section, examining relevant approaches for solving healthcare problems and identifying potential issues and inconsistencies.
COMPUTER COMMUNICATIONS
(2023)
Review
Mathematics
Shiyu Liu, Ou Liu, Junyang Chen
Summary: This paper reviews the latest techniques and applications of business analytics based on existing literature, and presents the current challenges faced by business analytics and open research directions that need further consideration.
Article
Multidisciplinary Sciences
Nattaphon Twinprai, Artit Boonrod, Arunnit Boonrod, Jarin Chindaprasirt, Wichien Sirithanaphol, Prinya Chindaprasirt, Prin Twinprai
Summary: In this study, a YOLOv4-tiny AI model was used to detect and classify hip fractures, and its performance was compared with human doctors. The results showed that the model had high sensitivity and accuracy in detecting hip fractures.
Review
Health Care Sciences & Services
Grazia Dicuonzo, Graziana Galeone, Matilda Shini, Antonella Massari
Summary: This article explores the application of big data in healthcare and the integration of traditional data analytical tools and techniques for decision-making. The study results suggest that the acquisition, management, and analysis of a large volume of health data are crucial for effective and patient-centered care.
Review
Education & Educational Research
Bahar Memarian, Tenzin Doleck
Summary: This article summarizes the pedagogical practices and tools used in data science education at the higher education level through a systematic literature review. The study finds that the content presented in data science education is diverse and difficult to compare. The study also examines the technological and pedagogical knowledge quality of the reviewed studies and lists the tools employed in each study.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Review
Pediatrics
Saheli Chatterjee Misra, Kaushik Mukhopadhyay
Summary: Big data analysis in pediatrics helps guide pediatricians in decision making and improves the surveillance, prevention, and performance of the health system. More work and the establishment of common databases are still needed in this field.
PEDIATRIC RESEARCH
(2023)
Article
Medicine, General & Internal
Noemi Gozzi, Edoardo Giacomello, Martina Sollini, Margarita Kirienko, Angela Ammirabile, Pierluca Lanzi, Daniele Loiacono, Arturo Chiti
Summary: This study utilized pretrained convolutional neural networks to identify abnormalities on chest radiographs, and evaluated their performance using an explainable AI model. The results showed that the best transfer learning model used image embeddings and random forest with simple averaging.
Editorial Material
Engineering, Electrical & Electronic
Rodney Brooks
Summary: Artificial intelligence has gone through several waves of investment, with early researchers predicting the arrival of human-level intelligent machines and exploring different technological paths. However, despite advancements in training algorithms and technology, intelligent machines have not yet been able to completely replace humans.
Article
Gastroenterology & Hepatology
Sheng Gao, Xiang Gao, Ruixin Zhu, Dingfeng Wu, Zhongsheng Feng, Na Jiao, Ruicong Sun, Wenxing Gao, Qing He, Zhanju Liu, Lixin Zhu
Summary: Dysbiosis of gut microbial community is associated with the pathogenesis of CD and may serve as a promising noninvasive diagnostic tool. We compared the performances of microbial markers at different biological levels and found that microbial genes were robust diagnostic biomarkers for CD. The gene model showed superior diagnostic capability and specificity for CD, and phosphotransferase system (PTS) played a significant role in its performance.
Editorial Material
Biochemical Research Methods
Guenther Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2016)
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Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2017)
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Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2016)
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Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2018)
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Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2018)
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Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2020)
Editorial Material
Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2020)
Editorial Material
Biochemical Research Methods
Gunter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2021)
Article
Biochemical Research Methods
Florian Schenk, Patricia Weber, Julian Vogler, Lars Hecht, Andreas Dietzel, Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2018)
Article
Biochemical Research Methods
Guenter Gauglitz
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2018)
