Mortality Prediction in the Emergency Service Intensive Care Patients with Possible COVID-19: A Retrospective Cross-Sectional Study by Mehmed Ulu, M. Kaya, Y. Tunc, H. Yildirim, A. Halici, A. Coskun

“…This study aims to determine the impact COVID-19 on mortality, evaluate the performance of Acute Physiology and Chronic Health Evaluation-2 Scores (APACHE II), Sequential Organ Failure Assessment Scores (SOFA) and Pneumonia Severity Index (PSI) for mortality prediction in the COVID-19 suspected patients. MATERIALS AND METHODS: This study is a retrospective cross-sectional analysis of patients who were admitted to the pandemic intensive care unit with possible COVID-19. 28-day mortality difference between positive and negative groups was defined as the primary outcome. …”
Get full text

Identification of m6A methyltransferase-related WTAP and ZC3H13 predicts immune infiltrates in glioblastoma by Liyun Gao, Jiaxin Gao, Jiayin He, Wenyan Fan, Xiangxin Che, Xin Wang, Tao Wang, Chunhua Han

Get full text

Assisting significance of lncRNA ASB16-AS1 in the early detection and prognosis prediction of patients with deep venous thrombosis by Menglan Li, Yingying Li, Dawei Zhang, Cheng Cheng, Meiying Yang, Xiuyin Zhang, Xinming Yu, Bo Lu, Min Wang

Get full text

Assessing the Impact of Modified Initial Abstraction Ratios and Slope Adjusted Curve Number on Runoff Prediction in the Watersheds of Sulaimani Province. by Farhan Ahmad Abdulrahman, Tarq Hama Karim

Get full text

A logistic regression model to predict long-term survival for borderline resectable pancreatic cancer patients with upfront surgery by Jin-Can Huang, Shao-Cheng Lyu, Bing Pan, Han-Xuan Wang, You-Wei Ma, Tao Jiang, Qiang He, Ren Lang

“…There still has been a debate about which predictive strategy is better in patients with borderline resectable pancreatic cancer (BRPC). …”
Get full text

A Novel Approach for Stock Price Prediction Using Gradient Boosting Machine with Feature Engineering (GBM-wFE) by Rebwar M. Nabi, Soran Ab. M. Saeed, Habibollah Harron

Subjects: “…Stock Market Forecasting, Feature Engineering Feature Selection Machine Learning Predictive Analysis Predictable Movement Multiclass Classification…”
Get full text

Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer by Xiaolong Liu, Pengxian Tao, He Su, Yulan Li

“…In conclusion, the prognosis model based on CRGs could be used as the basis for predicting the potential prognosis of patients with GC and provide new insights for the treatment of GC.…”
Get full text

RETRACTED ARTICLE: Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats by Jakob Steinfeldt, Benjamin Wild, Thore Buergel, Maik Pietzner, Julius Upmeier zu Belzen, Andre Vauvelle, Stefan Hegselmann, Spiros Denaxas, Harry Hemingway, Claudia Langenberg, Ulf Landmesser, John Deanfield, Roland Eils

Get full text

GNA15 predicts poor outcomes as a novel biomarker related to M2 macrophage infiltration in ovarian cancer by Qin Liu, Qin Liu, Yabing Sun, Yabing Sun, Tao Zhang, Wanrun Lin, Jing Zhang, Huijuan Zhang, Huijuan Zhang, Wenxin Zheng, Hong Xu, Hong Xu, Feng Zhou, Feng Zhou

“…An eight-gene prognostic model, including M2-like TAM-related genes, independently predicted poor outcomes in OC. GNA15 emerged as a hub gene positively correlated with M2-like TAMs infiltration, predicting unfavorable outcomes across OC cohorts. …”
Get full text

Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

Subjects: Get full text

Derivation of a simple risk calculator for predicting clinical worsening in patients with pulmonary hypertension due to interstitial lung disease by K. El-Kersh, R. Bag, N. Bhatt, C. King, A. Waxman, F. Rischard, H. Kim, D. Cella, E. Shen, SD Nathan

“…Our aim was to derive a simple and practical risk calculator that could be used to predict risk of clinical worsening in patients with ILD-PH. …”
Get full text

Construction and Validation of a Model for Predicting Fear of Childbirth: A Cross-Sectional Population Study via Machine Learning by Zhang ZL, Chen KJ, Chen H, Zhu MM, Gu JJ, Jiang LS, Zheng L, Zhou SG

Subjects: Get full text

Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework by Xinyu Guo, Faying Gu, Hongxu Liu, Yongcheng Yu, Runjie Li, Juan Wang

Subjects: “…Hierarchical economic model predictive control…”
Get full text

Prediction of Soil Organic Carbon Content in <italic>Spartina alterniflora</italic> by Using UAV Multispectral and LiDAR Data by Jiannan He, Yongbin Zhang, Mingyue Liu, Lin Chen, Weidong Man, Hua Fang, Xiang Li, Xuan Yin, Jianping Liang, Wenke Bai, Fuping Li

“…We compared the predictive performance of these different machine learning algorithms to identify the most effective one. …”
Get full text

Optic Nerve Sheath Diameter in Predicting the Neurological Outcomes of Cardiac Arrest Survivors: A Systematic Review and Meta-analysis by Parisa Jafari Khouzani, Erfan Rahmani, Mehdi Rezaei, Sasan Pohrbagher Benam, Atousa Moghadam Fard, Reza Amani-Beni, Maziar Daneshvar, Faezeh Jalayer Sarnaghy, Naghme Masoomi Goodarzi, Ramila Abedi Azar, Amirhossein Mirbolook, Peyman Bashghareh, Elham Bibak, Babak Goodarzi, Zahra Salarinezhad, Reza Zahedpasha, Marzieh Hajizaman, Negar Pourhossein Rahmani, Azam Darvishi, Alireza Hadizadeh, Fatemeh Zandi, Ashkan Azizi, Armin Naderi, Sepideh Shah Hosseini, Asie Sanjary, Mozhdeh Mohammadi Virsoudi, Habibollah Afshang, Seyedsaber Mirabdali, Navid Fathalian, Pouria Momeni, Mahsan Valizade, Fateme Nozari, Hamed Ghorbani, Sanam Mohammadzadeh, Seyed Kiavash Sajadi, Azam Abdollahi, Mehrdad Farrokhi

“…However, since the cut-off values and methods of ONSD measurement affect its predictive performance, further studies will be required to standardize these factors to achieve optimal predictive parameters. …”
Get full text

Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning by Alireza Hakimi, Parvin Ghafarian

“…Abstract Predicting wind speed simultaneously at multiple heights, particularly at 10 and 100 metres (m), presents unique challenges due to diverse influences. …”
Get full text

Enhancing climate resilience: A data-driven north rift weather prediction system for real-time forecasting and agricultural decision support by John W. Makokha, Peter W. Barasa, Geoffrey W. Khamala

Subjects: Get full text

The validity of the selection methods for recruitment to UK core psychiatry training: cohort study by Paul A. Tiffin, Emma Morley, Lewis W. Paton, Nandini Chakraborty, Fiona Patterson

Subjects: Get full text

Performance evaluation and prediction of optimal operational conditions for a compact date seeds milling unit using feedforward neural networks by Khaled Abdeen Mousa Ali, Changyou Li, Wang Han, Sali Issa, Mohamed Hamdy Eid, Samy F. Mahmoud, Marwa Abd-Elnaby Mohammed

“…With FNN model accuracy R2 of 0.99974, demonstrating high prediction reliability. Meanwhile, the operating cost was 0.027 $/kg, suitable for small to medium-scale operations. …”
Get full text

Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning by Junbo Liao, Yingxing Duan, Xiangwang Xu, Yaxue Liu, Chaohong Zhan, Gelei Xiao

“…Based on the CRRS model, an optimal comprehensive nomogram was created, exhibiting a favorable potential for predicting drug resistance in samples. Immune infiltration, cell–cell communication, and single cell analysis all indicated that high CRRS group was closely related to innate immune cells. …”
Get full text