Expression of EZH2 and H3K27me3 predicts tumor biology of urothelial carcinoma by Rasheeda Mohamedali, Suvradeep Mitra, Swarnendu Mandal, Prasant Nayak, Amit K. Adhya, Suvendu Purkait

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scCamAge: A context-aware prediction engine for cellular age, aging-associated bioactivities, and morphometrics by Vishakha Gautam, Subhadeep Duari, Saveena Solanki, Mudit Gupta, Aayushi Mittal, Sakshi Arora, Anmol Aggarwal, Anmol Kumar Sharma, Sarthak Tyagi, Rathod Kunal Pankajbhai, Arushi Sharma, Sonam Chauhan, Shiva Satija, Suvendu Kumar, Sanjay Kumar Mohanty, Juhi Tayal, Nilesh Kumar Dixit, Debarka Sengupta, Anurag Mehta, Gaurav Ahuja

“…Finally, we enhanced the generalizability of scCamAge by retraining it on human fibroblast senescence datasets, which improved its ability to predict senescent cells.…”
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Porto Alegre Line predicts lenticulostriate arteries encasement and extent of resection in insular gliomas. A preliminary study by Gustavo Rassier Isolan, Gustavo Rassier Isolan, Gustavo Rassier Isolan, Samir Ale Bark, Samir Ale Bark, Jander Moreira Monteiro, Jander Moreira Monteiro, Tobias A. Mattei, Kaan Yağmurlu, Rafaela Fernandes Gonçalves, Rafaela Fernandes Gonçalves, Osvaldo Malafaia, Rafael Roesler, Rafael Roesler, Rafael Roesler, Jurandir Marcondes Ribas Filho

“…We propose a new non-invasive method for LSTa involvement prediction in preoperative MRI (Porto Alegre Line). …”
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A Comparative Study of Hybrid Adaptive Neuro-Fuzzy Inference Systems to Predict the Unconfined Compressive Strength of Rocks by Annabelle Graham, Emma Scott

“…Performance indices such as R2, RMSE, NMSE, MAE, and n_10 index were used to assess the predictive capability of models indicating that ANAS with maximum  ÿ R2all=0.987 and minimum RMSEall=3.103, has the most optimal prediction performance for practical applications.…”
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Multiomic quantification of the KRAS mutation dosage improves the preoperative prediction of survival and recurrence in patients with pancreatic ductal adenocarcinoma by Won-Gun Yun, Daeun Kim, Youngmin Han, Wooil Kwon, Seong-Geun Lee, Jin-Young Jang, Daechan Park

“…The KRAS mutation dosage exhibited comparable performance with clinical variables for survival prediction. High KRAS mutation dosages activated the cell cycle, leading to high mutation rates and poor prognosis. …”
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A novel hybrid CLARA and fuzzy time series Markov chain model for predicting air pollution in Jakarta by Nurtiti Sunusi, Ankaz As Sikib, Sumanta Pasari

“…A 5 × 5 Markov transition probability matrix was subsequently constructed for modeling the data. Predicted values for SO₂ and CO in Jakarta using the CLARA-FTSMC hybrid method showed strong alignment with the actual data. …”
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Establishment of predictive models for head loss and filtration efficiency of pontoon mesh rotary filter based on dimension analysis by Zhen Jin, Lingwei Chen, Qiao Li, Mahemujiang Aihemaiti, Youwei Jiang, Hongfei Tao

“…The model exhibited high accuracy and could be used to predict the head loss and filtration efficiency of the pontoon mesh rotary filter. …”
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Integrative analysis of anoikis-related prognostic signature to evaluate the immune landscape and predict therapeutic response in stomach adenocarcinoma by Ziyi Zhou, Lanlan Yang, Yuan Fang, Rongzhong Xu, Xi Wang, Yuli Wang, Zhihong Fang

“…In summary, ARS can serve as a biomarker for predicting survival outcomes in STAD patients, providing new tools for personalized treatment decisions for STAD patients.…”
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Nutritional assessment using subjective global assessment identifies energy malnutrition and predicts mortality in patients with liver cirrhosis by Takao Miwa, Tatsunori Hanai, Kayoko Nishimura, Sachiyo Hirata, Shinji Unome, Yuki Nakahata, Kenji Imai, Atsushi Suetsugu, Koji Takai, Masahito Shimizu

“…Abstract This study aimed to evaluate whether the subjective global assessment (SGA) could effectively predict energy malnutrition, as assessed by indirect calorimetry, and mortality in hospitalized patients with cirrhosis. …”
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Novel Hybrid Radial-Based Neural Network Model for Predicting the Compressive Strength of Long-Term HPC Concrete by Hanlie Cheng, Shiela Kitchen, Graciela Daniels

“…The results conclude that the AORBF model can be preferred as an applicable model for compressive strength prediction.…”
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Training Load and Current Soreness Predict Future Delayed Onset Muscle Soreness in Collegiate Female Soccer Athletes by Brett S. Pexa, Christopher J. Johnston, Jeffrey B Taylor, Kevin R. Ford

“… # Conclusions Training load variables paired with the current day's DOMS significantly predict lower extremity DOMS in the future, with number of decelerations, accelerations, and HRmax best predicting future DOMS. …”
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Radiomic prediction for durable response to high‐dose methotrexate‐based chemotherapy in primary central nervous system lymphoma by Haoyi Li, Mingming Xiong, Ming Li, Caixia Sun, Dao Zheng, Leilei Yuan, Qian Chen, Song Lin, Zhenyu Liu, Xiaohui Ren

“…This study aimed to develop and validate radiomic‐based models to predict the durable response (DR) to high‐dose methotrexate (HD‐MTX)‐based chemotherapy in PCNSL patients. …”
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Elevated POSTN expression predicts poor prognosis and is associated with radioresistance in cervical cancer patients treated with radical radiotherapy by Cui-qin Huang, Wen-tao Xiao, Xiang-rong Yao, Zhi-min Li, Jun-yan He

“…A prognostic nomogram integrating POSTN expression and clinicopathological features demonstrated superior predictive accuracy for OS. Drug sensitivity analysis suggested that high POSTN expression may be linked to resistance to multiple chemotherapeutic agents. …”
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Cord Direct Antiglobulin Test for Predicting the Need for Phototherapy in Neonates with ABO Incompatibility: A Prospective Cohort Study by Ranjith Balan, Sakthipriya Balaji, Arun Kumar, Subash Sundar, Shrinidhi Krishnan, Ashok Chandrasekaran

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Protocol for predicting the single-cell network-based gene activity landscape during human B cell development by Xin Huang, Xuetong Hou, Yizhen Li, Jun J. Yang, Jiyang Yu

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The Cost of Regulating Effort: Reward and Difficulty Cues With Longer Prediction Horizons Have a Stronger Impact on Performance by Nanne Kukkonen, Senne Braem, Jens Allaert, Joshua O. Eayrs, Nicoleta Prutean, S. Tabitha Steendam, C. Nico Boehler, Jan R. Wiersema, Wim Notebaert, Ruth M. Krebs

“…In the random-dot-motion task, a high reward expectancy resulted in better accuracy, especially in easy trials, but only with long prediction horizon. Similarly, in the Stroop task, the reward facilitation of reaction time was only observed after reward cues with a long prediction horizon. …”
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Individualized drug therapy and survival prediction in ICU patients with acute kidney injury: construction and validation of a nomogram by Rui Yang, Xiaozhe Su, Ziqi Liu, Shuai Shao, Yinhuai Wang, Hao Su, Haiqing He

“…Conclusions In summary, the developed prediction model demonstrated accuracy for AKI patients in the ICU and helped clinical decision-making. …”
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Presenting a Prediction Model for CEO Compensation Sensitivity using Meta-heuristic Algorithms (Genetics and Particle Swarm) by Saeed Khaljastani, Habib Piri, Reza Sotoudeh

“…Given these points, the aim of this research is to provide a model for predicting the sensitivity of CEO compensation using meta-heuristic algorithms, specifically genetic algorithms and particle swarm optimization. …”
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The Implementation of a Support Vector Regression Model Utilizing Meta-Heuristic Algorithms for Predicting Undrained Shear Strength by Rami Al-Qasimi, Firas Al-Hajri

“…These results demonstrate the superiority of the SVNG model in providing precise and efficient predictions of USS, surpassing conventional methods.…”
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Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review by Yihun Mulugeta Alemu, Sisay Mulugeta Alemu, Dan Chateau, Nasser Bagheri, Kinley Wangdi

“…Background and objective This review compares non-laboratory-based and laboratory-based cardiovascular disease (CVD) risk prediction equations in populations targeted for primary prevention.Design Systematic review.Methods We searched five databases until 12 March 2024 and used prediction study risk of bias assessment tool to assess bias. …”
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