arXiv AI

Unveiling the Unborn: Advancing Fetal Health Classification through Machine Learning

arXiv:2310. 00505v3 Announce Type: replace-cross Abstract: Fetal health classification is a critical task in obstetrics, enabling early identification and management of potential health problems.

arXiv AI

Jul 2

Predicting Lethal Outcome (Cause) And Understanding Key Biomarkers Linked With Acute Myocardial Infarction Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

arXiv:2607. 00472v1 Announce Type: cross Abstract: Cardiovascular disease is still one of the main causes of death around the world.

By Sagnik Ghosh

arXiv AI

Jul 21

Investigation of Polycystic Ovary Syndrome (PCOS) Diagnosis Using Machine Learning Approaches

arXiv:2607. 16941v1 Announce Type: cross Abstract: Polycystic Ovarian Syndrome (PCOS) is a widespread hormone problem for women of childbearing age.

By Al Zadid Sultan Bin Habib, Md Asif Bin Syed, Md. Ekramul Islam, Tanpia Tasnim

arXiv AI

Jun 10

MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction

arXiv:2603. 02221v2 Announce Type: replace-cross Abstract: In clinical tabular prediction, classical machine learning models with feature engineering often outperform neural methods.

By Zizheng Zhang, Yiming Li, Justin Xu, Jinyu Wang, Rui Wang, Lei Song, Jiang Bian, David W Eyre, Jingjing Fu

llms benchmarks safety

arXiv AI

Jul 2

Prototype Memory-Guided Training-Free Anomaly Classification and Localization in Prenatal Ultrasound

arXiv:2607. 00744v1 Announce Type: cross Abstract: Prenatal anomaly classification and localization is of critical importance for fetal health and pregnancy management.

By Huanwen Liang, Yuhao Huang, Xiliang Zhu, Yuanji Zhang, Xuedong Deng, Xinru Gao, Guowei Tao, Yuhan Zhang, Dong Ni

fine-tuning

arXiv AI

Jul 13

A Personalized Computational Framework for Assessing the Sufficiency of Partially Observed Data in Healthcare AI models

arXiv:2607. 09165v1 Announce Type: cross Abstract: Achieving early and timely diagnosis and treatment for disease is a major challenge.

By Qingchu Jin, Felistas Mazhude, Jamie B. Rabb, Robert S. Kramer, Douglas B. Sawyer, Raimond L. Winslow

arXiv AI

Jun 30

CW-B: Class Weighted Boosting Framework for Imbalance Resilient Multi Class Cardiac Phenotyping

arXiv:2606. 29907v1 Announce Type: cross Abstract: Cardiac discharge phenotyping informs post-discharge treatment and follow-up, but real-world records are often incomplete and class-imbalanced, increasing the risk of missed high-risk phenotypes.

By Sijia Li, Xiaoyu Tan, Chen Zhan, Yuanji Ma, Haoyu Wang, Xihe Qiu

arXiv AI

Jun 2

LLMs for Cardiovascular Risk Prediction from Structured Clinical Data

arXiv:2606. 00031v1 Announce Type: cross Abstract: Coronary artery disease (CAD) remains one of the leading causes of death globally, highlighting the need for reliable predictive systems to support early diagnosis and risk assessment.

By Jeba Maliha, Md Rafiul Kabir

llms

arXiv AI

Jul 10

Predicting Male Fertility Using Machine Learning: A Semen Parameters Based Analysis with the VISEM Dataset

arXiv:2607. 08429v1 Announce Type: cross Abstract: Male infertility is a significant yet often underdiagnosed aspect of reproductive health, with semen analysis serving as the cornerstone of clinical evaluation.

By Shahnawaz Qureshi, Raja Khurram Shahzad, Muhammad Fozan, Emal Kawal, Syed Aziz Shah, Sattam Al-Anazi, Syed MuhammadZeeshan Iqbal

arXiv Machine Learning

Jul 28

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

arXiv:2607. 23412v1 Announce Type: new Abstract: Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, population, and measurement differences.

By Jie Lin, Weijie Sun, Sunil V. Kalmady, Anita Khalafbeigi, Abram Hindle, Padma Kaul, Russell Greiner

benchmarks

arXiv AI

Jun 16

Medical Heuristic Learning: An LLM-Driven Framework for Interpretable and Auditable Clinical Decision Rules

arXiv:2606. 16337v1 Announce Type: new Abstract: Predictive modeling for clinical tabular data is central to clinical decision support and therefore requires not only strong predictive performance but also transparent decision logic.

By Wei Xu, Ke Yang, Gang Luo, Keli Zheng, Lingyan Hu, Jing Wang, Kefeng Li

llms benchmarks

arXiv Machine Learning

Jun 19

Predicting gestational age at birth in the context of preterm birth from multi-modal fetal MRI

arXiv:2606. 20172v1 Announce Type: new Abstract: Preterm birth is associated with significant mortality and a risk for lifelong morbidity.

By Diego Fajardo-Rojas, Megan Hall, Daniel Cromb, Mary A. Rutherford, Lisa Story, Emma C. Robinson, Jana Hutter

multimodal benchmarks

arXiv AI

Jul 21

Benchmarking Machine Learning Models for Multi-Omics-Based Breast Cancer Prediction

arXiv:2607. 16250v1 Announce Type: cross Abstract: Estrogen Receptor (ER) status is a critical biomarker in breast cancer diagnosis, prognosis, and treatment selection.

By Priyanka Paudel, Madan Baduwal

efficiency benchmarks

Related stories