Supplementary materials for "Explainable ensemble machine learning for pregnancy screening in dairy cows using routine Dairy Herd Improvement records."

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…Read more

Resume Ranking Engine Using Machine Learning and Natural Language Processing for Automated Candidate Screening

V. Satish Mantripragada Akshaya Pranathi

Organizations often receive hundreds of resumes for a single job opening, making manual candidate screening slow and difficult to manage. Conventional recruitment methods generally depend on keyword matching or manual evaluation, both of which may overlook qualified applicants be…Read more

Village-Level Suitability Assessment For Litchi Cultivation In The Malwa Region Using Explainable Machine Learning And Geospatial Data

Dr. Pankaj Malik, Mishthi Patodia, Vedant soni, Deepika Kumari, Pragati Agrawal, Jaiswal Tanmay

Litchi is a high-value fruit crop traditionally cultivated in regions with favorable climatic and soil conditions. Expanding litchi cultivation into non-traditional areas such as the Malwa region of Madhya Pradesh requires accurate identification of suitable locations to minimize…Read more

A Systematic Review of Machine Learning, Deep Learning, and Explainable AI Approaches for Cardiac Disease Prediction

Sunanda Budihal, Sheetalrani Kawale, Abhishek Angadi

The cardiovascular (Cardiac) disease (CVD) is another factor that causes death among the global population most, and this is the reason why there is a high necessity to implement proper, effective, and interpretive diagnostic systems. The usage of machine learning (ML), deep lear…Read more

Also available via: European Organization for Nuclear Research

Simple Data Cleaning Techniques for Improving Machine Learning

Jyoti Panthangi

High-quality data is essential for building reliable machine learning models. Raw datasets often contain missing values, outliers, duplicates, inconsistent formats, and unstructured categorical variables. These issues reduce model accuracy and lead to biased predictions. This pap…Read more

Event-Based Prediction of Liquidity Sweep Dynamics in XAUUSD Using Machine Learning

Vanshvardhan Sharma

This paper develops a machine learning framework for detecting and predicting liquidity sweep events in XAUUSD using event-based market microstructure analysis. Using 15-minute data from 2014–2024, the study formalizes liquidity sweeps as a binary classification problem evaluated…Read more