Miroslav D. Dramićanin, Zoran Ristić, Jovana Periša, Aleksandar Ćirić, Milica Maričić, Anđela Rajčić, Tamara Gavrilović, Željka Antić
Samuel S Agboola, Oluwaseun E. Agboola, et al
Code and derived results for a study of whether the chemical transformations thatgenerate activity cliffs on one protein kinase predict cliffs on another. Matched molecular pairs were constructed from measured Ki and Kd binding affinitiesretrieved from ChEMBL (release 37) for 20…
Machine learning systems do not learn reality directly; they learn from the representations preserved in their datasets. This structured narrative review examines how dataset purpose, coverage, integrity, labeling, independence, reproducibility, governance, and continuity determi…
Grace Dooshima GBOR, Emmanuel Ogala, Donald Douglas Atsa’am, Iorshashe Agaji
Abstract The rapid growth of data-intensive applications has necessitated the development of scalable and efficient architectures for cloud-based machine learning and data analysis. This study proposes a scalable, distributed, and fault-tolerant architecture designed to address t…
Xin Wang, Guanglei Yao, Wei Ding
This archive contains the analysis code, the predictor dictionary, and the retrained primary model objects underlying the manuscript "Interpretable machine-learning risk stratification at the time of diagnosis for 3-year mortality in de novo metastatic prostate cancer: developmen…
Francesco Celino, Andrea Bricola
Age-gated applications need accurate, privacy-preserving age checks that run on-device, yet open-source age estimators remain too coarse for the adolescent band where false accepts matter most. We present Maestro (Machine-learning Age Estimator: Smart, Trustworthy, Responsive, On…
It provides (1) a harmonized multi-device soil-erosion database — 1,146 specimen records from EFA, SETD, JET, HET and related devices (1,013 with critical shear stress and 972 with erodibility coefficient), 186 raw erosion-rate-versus-shear-stress curves with power-law fits, and…