# Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers

arXiv: https://arxiv.org/abs/2406.12199 · HTML: https://mlsanity.com/paper/2406.12199/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- Builds on 41 of its 69 references that are in the map.
- First posted on arXiv 18 Jun 2024.

## Builds on (most cited first, 30 of 41)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://mlsanity.com/paper/2211.14730/) (2022)
- [TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis](https://mlsanity.com/paper/2210.02186/) (2022)
- [Temporal Convolutional Networks for Action Segmentation and Detection](https://mlsanity.com/paper/1611.05267/) (2016)
- [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://mlsanity.com/paper/2306.09364/) (2023)
- [Survival Prediction Across Diverse Cancer Types Using Neural Networks](https://mlsanity.com/paper/2404.08713/) (2024)
- [PLGSLAM: Progressive Neural Scene Represenation with Local to Global Bundle Adjustment](https://mlsanity.com/paper/2312.09866/) (2023)
- [Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review](https://mlsanity.com/paper/2402.10350/) (2024)
- [Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example](https://mlsanity.com/paper/2404.08279/) (2024)
- [A Study of the Attention Abnormality in Trojaned BERTs](https://mlsanity.com/paper/2205.08305/) (2022)
- [Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities](https://mlsanity.com/paper/2402.10835/) (2024)
- [Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate](https://mlsanity.com/paper/2402.02769/) (2024)
- [Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery](https://mlsanity.com/paper/1810.12813/) (2018)
- [ComposerX: Multi-Agent Symbolic Music Composition with LLMs](https://mlsanity.com/paper/2404.18081/) (2024)
- [Scaling Law for Time Series Forecasting](https://mlsanity.com/paper/2405.15124/) (2024)
- [Attention-Enhancing Backdoor Attacks Against BERT-based Models](https://mlsanity.com/paper/2310.14480/) (2023)
- [NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and Denoising](https://mlsanity.com/paper/2403.20034/) (2024)
- [AutoReP: Automatic ReLU Replacement for Fast Private Network Inference](https://mlsanity.com/paper/2308.10134/) (2023)
- [The FacT: Taming Latent Factor Models for Explainability with Factorization Trees](https://mlsanity.com/paper/1906.02037/) (2019)
- [Credit Card Fraud Detection Using Advanced Transformer Model](https://mlsanity.com/paper/2406.03733/) (2024)
- [MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training](https://mlsanity.com/paper/2312.08656/) (2023)
- [CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables](https://mlsanity.com/paper/2403.01673/) (2024)
- [Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithm](https://mlsanity.com/paper/2405.06652/) (2024)
- [Recurrent Neural Network from Adder's Perspective: Carry-lookahead RNN](https://mlsanity.com/paper/2106.12901/) (2021)
- [Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenes](https://mlsanity.com/paper/2404.06050/) (2024)
- [A Transformer-based Diffusion Probabilistic Model for Heart Rate and Blood Pressure Forecasting in Intensive Care Unit](https://mlsanity.com/paper/2301.06625/) (2023)
- [Research on Image Recognition Technology Based on Multimodal Deep Learning](https://mlsanity.com/paper/2405.03091/) (2024)
- [Infrared Image Super-Resolution via Lightweight Information Split Network](https://mlsanity.com/paper/2405.10561/) (2024)
- [DeepMTL Pro: Deep Learning Based MultipleTransmitter Localization and Power Estimation](https://mlsanity.com/paper/2112.13181/) (2021)
- [Predict Click-Through Rates with Deep Interest Network Model in E-commerce Advertising](https://mlsanity.com/paper/2406.10239/) (2024)

## Built on by (most cited first, 30 of 35)

- [Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach](https://mlsanity.com/paper/2408.06634/) (2024)
- [Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, and LLaMA](https://mlsanity.com/paper/2512.12812/) (2025)
- [Mitigating the Risk of Health Inequity Exacerbated by Large Language Models](https://mlsanity.com/paper/2410.05180/) (2024)
- [Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model](https://mlsanity.com/paper/2406.13987/) (2024)
- [Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods](https://mlsanity.com/paper/2408.04268/) (2024)
- [Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment Analysis](https://mlsanity.com/paper/2407.16150/) (2024)
- [Attention Mechanism and Context Modeling System for Text Mining Machine Translation](https://mlsanity.com/paper/2408.04216/) (2024)
- [XMeCap: Meme Caption Generation with Sub-Image Adaptability](https://mlsanity.com/paper/2407.17152/) (2024)
- [Research on reinforcement learning based warehouse robot navigation algorithm in complex warehouse layout](https://mlsanity.com/paper/2411.06128/) (2024)
- [Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN](https://mlsanity.com/paper/2408.03497/) (2024)
- [Recent Advancement of Emotion Cognition in Large Language Models](https://mlsanity.com/paper/2409.13354/) (2024)
- [Data Augmentation Through Random Style Replacement](https://mlsanity.com/paper/2504.10563/) (2025)
- [Style Transfer: From Stitching to Neural Networks](https://mlsanity.com/paper/2409.00606/) (2024)
- [Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model](https://mlsanity.com/paper/2410.17545/) (2024)
- [Integration of Mamba and Transformer -- MAT for Long-Short Range Time Series Forecasting with Application to Weather Dynamics](https://mlsanity.com/paper/2409.08530/) (2024)
- [LLM-Driven E-Commerce Marketing Content Optimization: Balancing Creativity and Conversion](https://mlsanity.com/paper/2505.23809/) (2025)
- [Test Time Learning for Time Series Forecasting](https://mlsanity.com/paper/2409.14012/) (2024)
- [Research on Cloud Platform Network Traffic Monitoring and Anomaly Detection System based on Large Language Models](https://mlsanity.com/paper/2504.17807/) (2025)
- [Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs](https://mlsanity.com/paper/2506.12182/) (2025)
- [GraphCNNpred: A stock market indices prediction using a Graph based deep learning system](https://mlsanity.com/paper/2407.03760/) (2024)
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- [Data-driven Probabilistic Trajectory Learning with High Temporal Resolution in Terminal Airspace](https://mlsanity.com/paper/2409.17359/) (2024)
- [Enhanced Credit Score Prediction Using Ensemble Deep Learning Model](https://mlsanity.com/paper/2410.00256/) (2024)
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- [Context-Aware Token Selection and Packing for Enhanced Vision Transformer](https://mlsanity.com/paper/2410.23608/) (2024)
- [TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration](https://mlsanity.com/paper/2502.17049/) (2025)
- [Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLM](https://mlsanity.com/paper/2506.07407/) (2025)
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- [Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)](https://mlsanity.com/paper/2409.16590/) (2024)

## Abstract (arXiv)

Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG. Traditional models, such as ARIMA and Prophet, are limited by their need for manual parameter tuning and challenges in handling noisy, sparse, and highly variable medical data. This study investigates advanced deep learning models, including LSTM, and transformer-based architectures, for predicting heart rate time series from the MIT-BIH Database. Results demonstrate that deep learning models, particularly PatchTST, significantly outperform traditional models across multiple metrics, capturing complex patterns and dependencies more effectively. This research underscores the potential of deep learning to enhance patient monitoring and CVD management, suggesting substantial clinical benefits. Future work should extend these findings to larger, more diverse datasets and real-world clinical applications to further validate and optimize model performance.