Evidence and gaps in clinical outcomes of novel pharmacologic therapies for sickle cell disease: A systematic literature review highlighting insights from clinical trials and real-... by Mohamed Yassin (4166515)

“…The high discontinuation rate and results of the STAND trial led to a significant decrease in the use of crizanlizumab. The HOPE trial demonstrated a 51 % improvement in hemoglobin response and a reduction in hemolytic markers in patients treated with voxelotor. …”

The value of amniotic fluid interleukin-6 determination in patients with preterm labor and intact membranes in the detection of microbial invasion of the amniotic cavity by Khoury, Alfred

“…Receiver-operator characteristic curve analysis, logistic regression analysis, and Cox's proportional-hazards model were used to explore the relationship between several explanatory and outcome variables. Diagnostic index values of interleukin-6, glucose level, Gram stain, leukocyte esterase; and limulus amebocyte lysate assay for prediction of a positive amniotic fluid culture, preterm delivery, clinical infection, and neonatal sepsis were calculated. …”
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Can plasma vitamin C predict survival in stage IV colorectal cancer patients? Results of a prospective cohort study by Temraz, Sally

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Development of Seed Variables Prediction Models for Use in Dynamic Backcalculation of FWD Data by Nasr, Cynthia

“…The OOB-Estimate of error rate and the overall accuracy values obtained dictate that the predictor variables selected to build the RF models are efficiently trained and generate accurate predictions for all seed variables except for the Rayleigh Damping Parameter of the PCC layer “”. …”
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Neutrophil‐to‐Lymphocyte Ratio Predicts Dialysis Timing & Prognosis in Critically Ill Patients by Abdulqadir J. Nashwan (11659453)

A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

“…This study proposes a hybrid scheme where two machine-learning (ML) models are coupled in a series to predict the PG value without any conclusive FP information. …”

The potential impact and diagnostic value of inflammatory markers on diabetic foot progression in type II diabetes mellitus: A case–control study by Amal Ahmed Mohamed (7121810)

“…The AUCs for CRP, IL-6, and HbA1c in predicting diabetic foot were 0.839, 0.728, and 0.834, respectively, demonstrating a good predictive value for each diagnostic marker. …”

Effectiveness of Positron Emission Tomography for Predicting Chemotherapy Response in Colorectal Cancer Liver Metastases by Glazer, Evan

“…When performed within 4 weeks of chemotherapy, PET had a negative predictive value of 13.3% and a positive predictive value of 94.3%. …”
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Quality Degradation And Pricing of Perishable Food Products by Alastal, Haya

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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…Experimental data was used to develop the appropriate architecture for the AAN using iterative steps of training and testing. Significant removals of chemical oxygen demand (COD) (89.2 to 98.3%), <i>NH</i>₄⁺ (88.5 to 98.9%), and total phosphorus (TP) (77.9 to 99.9%) were achieved at a total HRT of 13.3 h (HRT_Z-1 = 3 h, HRT_Z-2 = 6 h and HRT_Z-3 = 5.3 h) and an IRF value of 1.75. …”

Biochar yield prediction using response surface methodology: effect of fixed carbon and pyrolysis operating conditions by Sabah Mariyam (14150859)

“…An empirical equation is developed based on a statistically significant quadratic model to produce optimized biochar yield with high prediction accuracy. …”

Long Term HbA1c Prediction Using Multi-Stage CGM Data Analysis by Md Shafiqul Islam (7010348)

“…Accurate prediction of HbA1c can greatly improve the way diabetic patients are treated and can potentially avoid related consequences. …”

Hyperspectral-physiological based predictive model for transpiration in greenhouses under CO₂ enrichment by Ikhlas Ghiat (16932564)

“…The results demonstrated the inclusion of hyperspectral-based vegetation indices significantly increased the performance of the three machine learning models in predicting transpiration. …”

Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…A Friedman's test and Wilcoxon Sign-Rank post hoc analysis with Bonferroni correction show that PG prediction errors using GP are significantly lower than using the ANN model (p < 0.05). …”

Validation of the FASILA Score for Predicting Interventions and Outcomes in Traumatic Abdominal and Pelvic Injuries: A Prospective Clinical Study by Ayman El‐Menyar (17746911)

“…A FASILA score ≥ 4 had a high specificity (85.5%) and negative predictive value (80%) for predicting the need for surgery. …”

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…Various ML algorithms, such as Support Vector Machines, Logistic Regression, K-Nearest Neighbors, Naïve Bayes, Decision Trees, Random Forest, AdaBoost, Bagging, and Artificial Neural Networks are applied to predict student performance. SHAP values are used to interpret these predictions, offering insights into the factors most impacting student outcomes. …”
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Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach by Ahmad Abujaber (9100064)

“…<h3>Background</h3><p dir="ltr">The use of machine learning techniques to predict diseases outcomes has grown significantly in the last decade. …”

Validation of the emergency surgery score’s predictive accuracy for postoperative outcomes and ICU admissions in MENA vs. non-MENA emergency surgery patients by Mohamed Said Ghali (16810713)

“…<h3>Background</h3><p dir="ltr">The Emergency Surgery Score (ESS) has demonstrated strong predictive value for morbidity, mortality, and long-term survival outcomes. …”

Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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Prediction of Soil Loss in a Reservoir Watershed Using an Erosion Model and Modern Technological Tools: A Case Study of Marathon Lake, Attica in Greece by Pavlopoulos, Kosmas

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