Prediction of ACL Injuries from Vertical Jump Kinetics in Division 1 Collegiate Athletes by Marisa Pontillo, Shawn M Hines, Brian J Sennett

“…Logistic regression was used to determine if the battery of variables could predict whether or not an athlete would sustain an ACL injury. …”
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Cardiovascular disease risk prediction by Framingham risk score in women with polycystic ovary syndrome by Mina Amiri, Maryam Mousavi, Mahsa Noroozzadeh, Fereidoun Azizi, Fahimeh Ramezani Tehrani

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The Relationship Between Consumption Power and GDP Growth in China and Machine Learning Prediction Analysis by Hu Runsong

“…The paper examines the use of machine learning for predicting consumption capacity by integrating various economic models, including Support Vector Regression (SVR) and Long Short-Term Memory Network (LSTM). …”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…Abstract Background Drug-target binding affinity (DTA) prediction is vital in drug discovery and repositioning, more and more researchers are beginning to focus on this. …”
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An AI-based approach to predict delivery outcome based on measurable factors of pregnant mothers. by Michael Owusu-Adjei, James Ben Hayfron-Acquah, Twum Frimpong, Abdul-Salaam Gaddafi

“…Three supervised learning techniques are used and evaluated for performance. Prediction accuracy score of area under the curve obtained show Gradient Boosting classifier achieved 91% accuracy, Logistic Regression 93% and Random Forest 91%. …”
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The Predictive Value of the Pentraxin 3 Concentration in Cumulus Cell Culture Media for the Embryo Implantation by Tulay Irez, Yavuz Sahin, Eduard Malik, Onur Guralp

“…CONCLUSION: The cumulus cell culture medium Pentraxin 3 concentration was predictive for successful embryo implantation. Low Pentraxin 3 levels (<60 ng/mL were associated with failure of conception. …”
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Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction by Yue Peng, Junze Wu, Yi Sun, Yuanxing Zhang, Qiyao Wang, Shuai Shao

“…All experimentally verified effectors in Enterohemorrhagic Escherichia coli and 41 of 43 experimentally verified T3SEs of Salmonella Typhimurium are recognized. Moreover, 12 predicted T3SEs and 11 predicted T6SEs are validated by extensive experiments in Edwardsiella piscicida. …”
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Suggesting a Novel Hybrid Approach for Predicting Solar Irradiance in the Qinghai Province of China by Baran Yılmaz, Rachel Samra

“…This work aims to provide a hybrid model using machine learning to accurately predict solar Direct normal irradiance with the least amount of error. …”
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Photovoltaic-Power Prediction Model Based on Quantum Long Short-Term Memory Network by PAN Dong, YANG Xin, SHI Tiancheng, FANG Yuan, WANG Xuli, DOU Menghan

Subjects: “…quantum computer|quantum long short-term memory network|dual-stage attention|photovoltaic power prediction…”
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Can the Risk Factors Predicting Surgical Treatment be Determined in Patients with Tubo-Ovarian Abscess? by Tayfun Vural, Burak Bayraktar, Suna Yildirim Karaca, Emir Gurbuz, Mehmet Ozeren, Cuneyt Eftal Taner

“… OBJECTIVES: In this study, we aimed to determine the risk factors in predicting the need for surgical treatment due to medical treatment failure in patients with tubo-ovarian abscess. …”
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A prediction model for sleep disorders in shift workers of a chemical fiber enterprise by SHEN Lili, PAN Yahui, FENG Jiafeng

“…Objective: To construct a prediction model for sleep disorders in shift workers of a chemical fiber enterprise, so as to provide the basis for early identification and prevention of sleep disorders in shift workers. …”
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Real-Time Pose Prediction and Dynamic Anchor Selection for Ultra-Wideband Tagless Gate by Junyoung Choi, Joohyun Lee, Sagnik Bhattacharya

“…In this paper, we propose dynamic anchor selection for extremely accurate DL-TDoA localization and pose prediction for DS-TWR, called DynaPose. Based on the channel impulse response of UWB, DynaPose classifies the signal condition, such as line-of-sight (LOS) and non-LOS (NLOS), using deep learning models. …”
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Using machine learning models to plan HIV services: Emerging opportunities in design, implementation and evaluation by T Dzinamarira, E Mbunge, I Chingombe, D F Cuadros, E Moyo, I Chitungo, G Murewanhema, B Muchemwa, G Rwibasira, O Mugurungi, G Musuka, H Herrera

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Current and future burden of breast cancer in Asia: A GLOBOCAN data analysis for 2022 and 2050 by Mengxia Fu, Zhiming Peng, Min Wu, Dapeng Lv, Yanping Li, Shuzhen Lyu

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Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases by K. A. Muthukumar, Dhruva Nandi, Priya Ranjan, Krithika Ramachandran, Shiny PJ, Anirban Ghosh, Ashwini M, Aiswaryah Radhakrishnan, V. E. Dhandapani, Rajiv Janardhanan

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Frontal Pole, Cingulate Gyrus, and Precuneus Cortex Represent the Confidence Level in Prediction of Other's Risky Decision-Making. by Ahmad Shoaa Haghighi, Soroush Safari, Elahe Oloumi, Hadis Jameei, Gholam Ali Hossein Zadeh, Abdol-Hossein Vahabie

Subjects: “…Confidence level; Prediction; Metacognition; Decision-making.…”
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Artificial Intelligence (AI) for Crop Yield Forecasting by Clyde Fraisse, Yiannis Ampatzidis, Sandra Guzmán, Wonsuk Lee, Christopher Martinez, Sanjay Shukla, Aditya Singh, Ziwen Yu

Subjects: “…yield prediction…”
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SHASI-ML: a machine learning-based approach for immunogenicity prediction in Salmonella vaccine development by Ottavia Spiga, Ottavia Spiga, Ottavia Spiga, Anna Visibelli, Francesco Pettini, Bianca Roncaglia, Annalisa Santucci, Annalisa Santucci, Annalisa Santucci

“…IntroductionAccurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly for Salmonella infections which remain a significant global health challenge.MethodsWe developed SHASI-ML, a machine learning-based framework for predicting immunogenic proteins in Salmonella species. …”
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Comparison of frailty instruments for predicting mortality and prolon ged hospitalization in acute coronary syndrome patients. by Anne Langsted, Jocelyne Benatar, Andrew Kerr, Katherine Bloomfield, Gerry Devlin, Alexander Sasse, David Smythe, Andrew To, Harvey White, Gerrard Wilkins, Ralph Stewart

“…<h4>Objective</h4>To evaluate the relative strengths of 3 frailty assessment instruments for predicting mortality and prolonged hospitalization in acute coronary syndrome patients.…”
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Sequential Organ Failure Assessment score in predicting the prognosis of necrotising fasciitis: a prospective study by Rajshekar Puttaswamy, Deepak Ghuliani, Shruti Sharma, P Lohith, RK Jindal, Sushanto Neogi, Mohak Singh

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