Systems Predictive Modeling for Enrollment and Student Success in Institutional Decision Systems

Data-driven predictive models help institutions improve enrollment planning and student outcomes. #predictivemodeling

What if your predictive model is limiting performance?

We found that a model built for business forecasting isn't always the right one to guide bidding in ad networks.

If you rely on predictive modeling, this is worth a read, tinyurl.com/4xy9tzds.

#PredictiveModeling #PaidMedia

Research and development, supply chain management and clinical outcomes are all being transformed by predictive insights. Effectively managing this data is challenging, but when organizations succeed, it becomes a powerful driver of progress. taxodiary.com?p=57659 #PredictiveModeling #LifeSciences

Artificial Intelligence–Enhanced Multi-Algorithm R Shiny Application for Predictive Modeling and Analytics: Case Study of Alzheimer Disease Diagnostics Background: AI has demonstrated superior diagnostic accuracy compared to medical practitioners, highlighting its growing importance in healthcare. SMART-Pred (Shiny Multi-Algorithm R Tool for Predictive Modeling) is an innovative AI-based application for Alzheimer's disease (AD) prediction using handwriting analysis. Objective: To develop and evaluate a non-invasive, cost-effective AI tool for early AD detection, addressing the need for accessible and accurate screening methods. Methods: The study employed Principal Component Analysis (PCA) for dimensionality reduction of handwriting data, followed by training and evaluation of ten diverse AI models, including logistic regression, Naïve Bayes, random forest, AdaBoost, Support Vector Machine (SVM), and neural network. Model performance was assessed using accuracy, sensitivity, specificity, F1-score, and ROC-AUC metrics. The DARWIN dataset, comprising handwriting samples from 174 participants (89 AD patients, 85 healthy controls) was used for validation. Results: The Neural Network classifier achieved an accuracy of 91% with a 95% CI ranging from 0.79-0.97 and an AUC of 92%, on the test set after identifying the most significant features for AD prediction. These results surpass current clinical diagnostic tools, which typically achieve around 81% accuracy. SMART-Pred's performance aligns with recent AI advancements in AD prediction, such as the Cambridge scientists' AI tool achieving 82% accuracy in identifying AD progression within three years using cognitive tests and MRI scans. The variables "air_time" and "paper_time" consistently emerged as critical predictors for AD across all ten AI models, highlighting their potential importance in early detection and risk assessment. To augment transparency and interpretability, we incorporated the principles of explainable AI, specifically using SHapley Additive exPlanations (SHAP) values—a state-of-the-art method to emphasize the features responsible for our model’s efficacy. Conclusions: SMART-Pred offers non-invasive, cost-effective, and efficient AD prediction, demonstrating the transformative potential of AI in healthcare. While clinical validation is necessary to confirm the practical applicability of the identified key variables, this study contributes to the growing body of research on AI-assisted AD diagnosis and may lead to improved patient outcomes through early detection and intervention.

New in JMIR Aging: Artificial Intelligence–Enhanced Multi-Algorithm R Shiny Application for Predictive Modeling and Analytics: Case Study of Alzheimer Disease Diagnostics #ArtificialIntelligence #PredictiveModeling #AlzheimerDiagnosis #HealthcareInnovation #MachineLearning

Correction: Structural and Functional Impacts of SARS-CoV-2 Spike Protein Mutations: Insights From Predictive Modeling and Analytics #SARSCoV2 #SpikeProtein #COVID19 #VirusMutations #PredictiveModeling

Sign that reads "Where innovation flows, possibility follows."

Sign that reads "Water isn't just a resource, it's our responsibility."

IDWS 2025 reinforced that innovation = technology + policy + knowledge. Proud to see this strategic transformation coming to life!

#WaterSustainability #PredictiveModeling #NeurosciencePolicy #KAUST #Jeddah #Vision2030

Structural and Functional Impacts of SARS-CoV-2 Spike Protein Mutations: Insights From Predictive Modeling and Analytics Background: The COVID-19 pandemic requires a deep understanding of SARS-CoV-2, particularly how mutations in the Spike Receptor Binding Domain (RBD) Chain E affect its structure and function. Current methods lack comprehensive analysis of these mutations at different structural levels. Objective: To analyze the impact of specific COVID-19 associated point mutations (N501Y, L452R, N440K, K417N, E484A) on the SARS-CoV-2 Spike RBD structure and function using predictive modeling, including a graph-theoretic model, protein modeling techniques, and molecular dynamics simulations. Methods: The study employed a multi-tiered graph-theoretic framework to represent protein structure across three interconnected levels. This model incorporated 19 top-level vertices, connected to intermediate graphs based on 6-angstrom proximity within the protein's 3D structure. Graph-theoretic molecular descriptors/invariants were applied to weigh vertices and edges at all levels. The study also used Iterative Threading Assembly Refinement (I-TASSER) to model mutated sequences and molecular dynamic simulation (MD) tools to evaluate changes in protein folding and stability compared to the wildtype. Results: Three distinct predictive modeling and analytical approaches successfully identified structural and functional changes in the SARS-CoV-2 Spike RBD (Chain E) resulting from point mutations. The novel graph-theoretic model detected notable structural changes, with N501Y and L452R showing the most pronounced effects on conformation and stability compared to the wildtype. K147N and E484A mutations demonstrated less significant impacts compared to the severe mutations, N501Y and L452R. Ab initio modeling and molecular simulation dynamics findings corroborated the results from graph-theoretic analysis. The multi-level analytical approach provided a comprehensive visualization of mutation effects, deepening our understanding of their functional consequences. Conclusions: This study advanced our understanding of SARS-CoV-2 Spike RBD mutations and their implications. The multi-faceted approach characterized the effects of various mutations, identifying N501Y and L452R as having the most substantial impact on RBD conformation and stability. The findings have important implications for vaccine development, therapeutic design, and variant monitoring. Our research underscores the power of combining multiple predictive analytical approaches in virology, contributing valuable knowledge to ongoing efforts against the COVID-19 pandemic and providing a framework for future studies on viral mutations and their impacts on protein structure and function.

Structural and Functional Impacts of SARS-CoV-2 Spike Protein Mutations: Insights From Predictive Modeling and Analytics #COVID19 #SARSCoV2 #SpikeProtein #MutationResearch #PredictiveModeling

Efficacy, safety and exploratory analysis of neoadjuvant tislelizumab (a PD-1 inhibitor) plus nab-paclitaxel followed by epirubicin/cyclophosphamide for triple-negative breast cancer: a phase 2 TREND trial - Signal Transduction and Targeted Therapy Signal Transduction and Targeted Therapy - Efficacy, safety and exploratory analysis of neoadjuvant tislelizumab (a PD-1 inhibitor) plus nab-paclitaxel followed by epirubicin/cyclophosphamide for...

Neoadjuvant #tislelizumab combined with nab-paclitaxel and #anthracycline-based #chemotherapy is safe and effective in #TNBC, achieving high pCR, with multi-omics analyses revealing #immune pathways and enabling #PredictiveModeling.

#STTT #OpenAccess:

Congrats @lukeguerdan.bsky.social and co-authors of "Measurement as Bricolage: Examining How Data Scientists Construct Target Variables for Predictive Modeling Tasks."

#cscw2025 #cmuhcii #HCI #DataScience #ML #PredictiveModeling #ComputerScience

Neoadjuvant #tislelizumab combined with nab-paclitaxel and #anthracycline-based #chemotherapy is safe and effective in #TNBC, achieving high pCR, with multi-omics analyses revealing #immune pathways and enabling #PredictiveModeling.

#STTT #OpenAccess: doi.org/10.1038/s413...

Good read from @benjaminsmanning.bsky.social & @johnjhorton.bsky.social! Using human data + smart simulations, they show how AI can handle new situations better, a big step for social science.
#AI #AIAgents #SocialScience #MIT #PredictiveModeling #ResearchSky #AcademicSky

🕸️ Why AI's Next Breakthrough Isn't About More Data: #MKAN

www.buzzsprout.com/2405788/epis... 

helioxpodcast.substack.com/publish/post... 


#AI #MachineLearning #DataScience #ScientificComputing #TechInnovation #ComputationalScience #PredictiveModeling #DeepLearning #PhysicsInformedML

How are you leveraging advanced analytics to transform your VBC initiatives and proactively manage patient outcomes?

#ValueBasedCare #HealthcareAnalytics #PredictiveModeling #RiskAdjustment #DataScience #PopulationHealth #HealthTech

Accelerate decision-making and innovation with custom data science and ML solutions—predict trends, optimize operations, and personalize experiences.

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#DataAnalytics #AItools #PredictiveModeling #MLservices #InsightDriven

🚨 PhD Fellowship Opportunity in instrumental genetics and microbiome-based multiomics integration analyses and predictive modeling! 🌱🧬🔬
📢 Apply now or share with those who might be interested!
#PhDOpportunity #Bioinformatics #PredictiveModeling
idibgi.org/treball/fi-a...

Artificial intelligence in cardiovascular procedures: a... : Annals of Medicine and Surgery ines research trends, key contributors, and emerging themes in AI-driven cardiovascular interventions. Methods: We retrieved relevant publications from the Web of Science Core Collection and analyz...

#AI is rapidly transforming cardiovascular procedures—from diagnosis to surgery. Our bibliometric study shows booming global research, with top themes like #MachineLearning & #PredictiveModeling. Big potential for improved outcomes! #CardiovascularSurgery journals.lww.com/annals-of-me...

Predicting Clinical Trial Success with Machine Learning Learn how machine learning in R predicts clinical trial success with 85% accuracy. Improve drug development strategy, reduce costs, and enhance portfolio ROI.

Predicting Clinical Trial Success with Machine Learning
wp.me/p5ALE7-1ku

#biotechdatascience #machinelearninginR #PharmaAnalytics #predictivemodeling #clinicaltrialprediction #healthcareAI #notable

Communemashin YouTube video by SRWeaver: Banquest De Cendres

youtu.be/ZfvKhsgPGYk

This is for predictive player, digital pet, and enemy behaviors over time.

#interactivefiction #predictivemodeling #textadventures #bequestdecendresframework

Colorado Springs Implements Power BI for Enhanced Data Visualization and Management Colorado Springs utilizes Power BI to improve data extraction and visualization processes.

Hillsborough County is revolutionizing data management with a groundbreaking predictive modeling tool that promises to enhance decision-making and community engagement!

Learn more here!

#HillsboroughCounty #FL #CommunityCollaboration #CitizenPortal #PredictiveModeling #DataManagement

DeKalb County analyzes aging pipe vulnerabilities using advanced modeling techniques Experts assess corrosion risks and failure patterns of various pipe materials in DeKalb County.

Hillsborough County officials are diving deep into advanced predictive modeling techniques to tackle aging pipeline vulnerabilities, revealing how various materials can dramatically impact infrastructure integrity.

Click to read more!

#HillsboroughCounty #FL #CitizenPortal #PredictiveModeling

Ethan Kearsey leads PS25-28 predictive modeling meeting on pipeline failures Committee discusses predictive modeling for pipeline failure risks during public meeting.

Hillsborough County is taking bold steps to enhance public safety by unveiling a groundbreaking predictive modeling project aimed at preventing pipeline failures.

Learn more here!

#HillsboroughCounty #FL #CitizenPortal #PublicSafety #InfrastructureReliability #PredictiveModeling

Hartford MDC implements advanced VOTA AI model for pipeline failure prediction Hartford MDC enhances pipeline management using VOTA AI for better failure prediction accuracy.

Hillsborough County is revolutionizing pipeline safety with cutting-edge predictive modeling, achieving a remarkable 55% improvement in failure prediction accuracy!

Click to read more!

#HillsboroughCounty #FL #CitizenPortal #PredictiveModeling #InfrastructureSafety #WaterManagement

SAWS Implements Machine Learning for Water Main Replacement Planning Success SAWS utilizes machine learning for accurate water main replacement predictions over 7500 miles.

Hillsborough County is revolutionizing its pipeline management with cutting-edge predictive models to ensure safer, more reliable water and sewer systems for residents.

Learn more here!

#HillsboroughCounty #FL #CitizenPortal #InfrastructureReliability #PredictiveModeling #DataDrivenDecisions

Arcadis Presents Predictive Modeling for Pipeline Failures to Hillsborough County Water Resources Arcadis showcases machine learning capabilities for pipeline failure prediction in presentation.

Hillsborough County is revolutionizing its pipeline safety with cutting-edge predictive modeling that could prevent future failures and enhance water management!

Learn more here

#HillsboroughCounty #FL #CitizenPortal #PublicSafety #PredictiveModeling #WaterResourceManagement

Arcadis presents innovative asset management strategies for JEA water systems Arcadis showcases machine learning tools and comprehensive plans for water asset management.

Hillsborough County is on the brink of a water management revolution as Arcadis unveils groundbreaking predictive models to transform pipeline management and prevent failures.

Click to read more!

#HillsboroughCounty #FL #CitizenPortal #PredictiveModeling #WaterSystems #InfrastructureManagement

alvaQSARを使ってみました alvaQSARの試用レポート

📢 See alvaQSAR in action.

Our partner Affinity Science has just published a hands-on review (in Japanese) of alvaQSAR.

🔗 Read the article: www.affinity-science.org/2025/07/alva...
🌐 More on #alvaQSAR: www.alvascience.com/alva/qsar/

#QSAR #Cheminformatics #Toxicology #PredictiveModeling

Fluctuation structure predicts genome-wide perturbation outcomes
Goyal, Y., Haley, B. et al.
Paper
Details
#GenomeResearch #Bioinformatics #PredictiveModeling

RPS25-208 evaluation committee ranks AECOM first with 95 points Committee evaluates proposals with AECOM receiving the highest score in the review.

Hillsborough County is taking major steps to prevent pipeline failures, with AECOM leading the pack in a crucial evaluation process that could shape the future of public safety.

Click to read more!

#HillsboroughCounty #FL #CitizenPortal #PredictiveModeling #CivicAccountability

Something #bizarre...
The Future Out of Time:
medium.com/@author_jcaf...

#TRUESTORY #weird #predictiveanalytics #paranormal #fortuneteller #prediction #telepathy #clairvoyant #empath #psychic #seer #profit #prophecy #predictivemodeling #parapsychology #supernatural

Why SAS A00–226 Certification Can Elevate Your Analytics Career Organizations are awash in data, but transforming raw information into actionable insights remains a critical challenge. Professionals who…

SAS A00-226: Analytics Career Catalyst! Discover how this certification can supercharge an analytics career.

Advanced modeling skills validated
New career avenues
Professional impact

medium.com/@certifyinsi...

#A00_226 #DataScience #PredictiveModeling #SasTextAnalytics #SASCertification