This article examines the work of data scientist Sai Prashanth Pathi in AI for credit risk, focusing on explainable machine ...
Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.
The conversion of carbon dioxide into clean fuels is regarded as an important route toward carbon neutrality. CO 2 methanation, in particular, has drawn increasing interest due to its favorable ...
Analysis of the 191 samples shows that 55 percent of groundwater falls within low to no restriction categories for irrigation ...
This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...
Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...
Medulloblastoma the most common malignant pediatric brain tumor with a high risk of metastasis and poor survival outcomes. To delineate the metastatic microenvironment,, researchers in China have ...
Krishna, Satyapriya, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Transactions on ...
Recent research is advancing seismic hazard modeling through AI-driven soil liquefaction prediction, interpretable machine learning, physics-based simulations, and waveform-based probabilistic ...
Inogic has introduced three AI-powered solutions for Microsoft Dynamics 365 CRM to strengthen predictive analytics, intelligent document search, and context-aware recommendations. Using Azure Machine ...
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