Feature Engineering

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Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering
Aug 6, 2026Soorya Ram Shimgekar, Michelle Hu, Dorisa Shehi +10Cardiac Electronic Health Records
When Do Corrective Features Help? An Agent for Corrective Feature Discovery on Black-Box Forecasters
Aug 5, 2026Fangxin Wang, Ziyi Zhang, Diyi Zhuang +4Feature Engineering Post-Hoc
ScaFE: Data-Efficient Scar Classification with LLM-Generated Clinical Feature Programs
Jul 30, 2026Ruman Wang, Hangting YeSkin Lesion Classification Medical Imaging
Adaptive Graph-of-Islands Evolution for Automatic Feature Engineering with LLMs
Jul 25, 2026Sha Li, Naren RamakrishnanFeature Engineering Tabular Learning
Format-Controlled Multi-Scale JPEG Compression Response Analysis for Image-Level Forgery Screening
Jul 7, 2026Sujith K MandalaFace Forgery Detection Lighting Artifacts
From Textural Counterpoint to Feature Encoding: A Multi-Dimensional Machine Representation Study of Haydn's "The Lark" Integrating Electroacoustic Analysis
Jul 7, 2026Yakun Liu, Zhiyu Jin, Hai Luan +2Music Generation Acoustic Representation
COMET: Combinatorial Optimization for Multiplex Editing Targets Via Constraint-Preserving QAOA
Jul 2, 2026Priyansh Singhal, Sumit Maheshwari, Piyush JoshiQuantum Approximate Optimization Algorithm Quantum
Evolutionary Feature Engineering for Structured Data
Jul 2, 2026Ege Onur Taga, Yilin Zhuang, M. Emrullah Ildiz +4Feature Engineering Evolution
Interpretable vs Learned Encoders for High-Cardinality Fraud Detection
Jul 1, 2026Xiao Han, Jingjing Liu, Moxuan Zheng +2Fraud Detection Feature Engineering
Rethinking the Role of Feature Engineering and Learning Strategies in Few-Shot Hidden Emotion Recognition
Jun 30, 2026Xiaochuan Guo, Jihao Gu, Haixu Liu +6Emotion Recognition Temporal Learnability
When LLMs Analyze Scars: From Images to Clinically-Meaningful Features
Jun 16, 2026Ruman Wang, Hangting YeSkin Lesion Classification Image Classification
A Universal Dense Football Event Representation Based on TabTransformer
Jun 8, 2026Weiran Yang, Daniel Memmert, Maximilian Klemp-WeinsSports Analytics Spatio-Temporal Transformers
LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version)
Jun 8, 2026Ankai Hao, Ke Chen, Huan Li +1Feature Engineering Taco
Bridging Expert Knowledge and Automated Feature Engineering via Self-Evolution
Jun 7, 2026Varun Khurana, Vijval Ekbote, Vashu Chauhan +3Feature Engineering Feature Extraction
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Jun 1, 2026Andrej Tschalzev, Nick Erickson, Yuyang Wang +4Tabular Learning Feature Engineering
Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction
May 24, 2026Hangxuan Li, Renjun Jia, Xuezhang Wu +3Feature Engineering Predictive Performance
TabKDE: Simple and Scalable Tabular Data Generation with Kernel Density Estimates
May 17, 2026Meysam Alishahi, Yan Zheng, Junpeng Wang +2Synthetic Tabular Data Gaussian Copula
Language Modeling with Hyperspherical Flows
May 11, 2026Justin Deschenaux, Caglar GulcehreDiffusion Language Models Speech Language Models
Optimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning
May 9, 2026Emmanuel AdutwumHyperparameter Feature Importance
Does Your Neural Network Extrapolate? Feature Engineering as Identifiability Bias for OOD Generalization
May 8, 2026Leonel Aguilar, Jan Nagler, Christoph Hoelscher +1Feature Learning Overfitting
Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding
May 6, 2026Taiga Hayashi, Yuya Seki, Kotaro Terada +3Exploratory Factor Analysis Cosine Annealing
SCOPE-FE: Structured Control of Operator and Pairwise Exploration for Feature Engineering
Apr 29, 2026Minhee Park, Seongyeon Son, Yonghyun Lee +1Feature Engineering Tabular Learning
FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records
Apr 24, 2026Hojjat Karami, David Atienza, Jean-Philippe Thiran +1Electronic Health Records Feature Engineering
CoFEE: Reasoning Control for LLM-Based Feature Discovery
Apr 23, 2026Maximilian Westermann, Ben Griffin, Aaron Ontoyin Yin +6LLM Reasoning Methods Feature Engineering
Memory-Augmented LLM-based Multi-Agent System for Automated Feature Generation on Tabular Data
Apr 22, 2026Fengxian Dong, Zhi Zheng, Xiao Han +5Feature Engineering Memory-Augmented Large Language Models

Aug 6, 2026 · cs.AIJ/K move · Enter open · S save

Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering

Soorya Ram Shimgekar, Michelle Hu, Dorisa Shehi, Daniel Kang+9

Nimblemind · Singapore University of Technology and Design · University of Illinois Urbana-Champaign · Florida International University · University of California Los Angeles

Electronic health record (EHR) feature engineering is a major bottleneck in clinical research and AI, accounting for 39-45% of data scientists' workload. This is especially pronounced in heart failure, which affects an estimated 6.7 million U.S. adults and requires integrating fragmented EHR data with disease-specific, guideline-based clinical reasoning. Existing rule-based and large language model (LLM)-based approaches offer only partial automation with limited maintainability and evidence traceability. We developed the Nimblemind Multi-Agent System (nMAS), an evidence-linked, rubric-grounded pipeline for automated heart-failure feature engineering, and evaluated it on 500 dummy patient records from nine EHR source tables. nMAS generated 132 structured and 70 rubric-scored aggregated features, verified for structural integrity, rubric compliance, and provenance, and audited by a restricted LLM. Adding the aggregated features improved held-out AUROC from 0.895 to 0.963 for HFrEF and 0.870 to 0.910 for HFpEF phenotyping, and an independent LLM-based rubric assessment of evidence support and methodological soundness scored the features at 81.5% of maximum points. These results demonstrate the feasibility of automated, auditable feature engineering for complex cardiovascular EHR data, though evaluation was limited to a single-institution cohort and external validation is needed.

Cardiac Electronic Health Records Electrocardiogram Feature Engineering Clinical Reasoning

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