severity prediction

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

29 shown of 29 papers with code (67 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software
  19 Jul 2021 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Data-driven research on the automated discovery and repair of security vulnerabilities in source code requires comprehensive datasets of real-life vulnerable code and their fixes.
• CNN-LSTM Hybrid Model for AI-Driven Prediction of COVID-19 Severity from Spike Sequences and Clinical Data
  29 May 2025 1 repository listed
  Conclusion: The CNN-LSTM hybrid model effectively predicted COVID-19 severity using spike protein sequences and clinical data, highlighting the utility of AI in genomic surveillance and precision public health.
• Diagnosing COVID-19 Severity from Chest X-Ray Images Using ViT and CNN Architectures
  23 Feb 2025 1 repository listed
  The COVID-19 pandemic strained healthcare resources and prompted discussion about how machine learning can alleviate physician burdens and contribute to diagnosis.
• K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction
  18 Feb 2025 1 repository listed
  For instance, Tx-Gemma 27B improves by 19.
• Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networks
  2 Dec 2024 1 repository listed
  By training shallow network architectures and minimizing the number of selected features, the framework produces lightweight models that deliver explainable results through feature attribution and symbolic…
• HCT: Hybrid Convnet-Transformer for Parkinson's disease detection and severity prediction from gait
  26 Oct 2023 1 repository listed
  Our hybrid architecture exploits the strengths of both Convolutional Neural Networks (ConvNets) and Transformers to accurately detect PD and determine the severity stage.
• A generalized framework to predict continuous scores from medical ordinal labels
  30 May 2023 1 repository listed
  These labels are used to train and evaluate disease severity prediction models.
• An Ensemble Deep Learning Approach for COVID-19 Severity Prediction Using Chest CT Scans
  17 May 2023 1 repository listed
  Chest X-rays have been widely used for COVID-19 screening; however, 3D computed tomography (CT) is a more effective modality.
• TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks
  17 Apr 2023 1 repository listed
  To bridge this gap, we have constructed a real-world graph-based Traffic Accident Prediction (TAP) data repository, along with two representative tasks: accident occurrence prediction and accident severity prediction.
• Dynamic Healthcare Embeddings for Improving Patient Care
  21 Mar 2023 1 repository listed
  Here, we propose DECENT, an auto-encoding heterogeneous co-evolving dynamic neural network, for learning heterogeneous dynamic embeddings of patients, doctors, rooms, and medications from diverse data streams.
• 2D and 3D CNN-Based Fusion Approach for COVID-19 Severity Prediction from 3D CT-Scans
  15 Mar 2023 1 repository listed
  CT-scan imaging is the most informative tool about this disease.
• Predicting crash injury severity in smart cities: a novel computational approach with wide and deep learning model
  4 Mar 2023 1 repository listed
  Smart cities came out as highly knowledgeable bio-networks, offering intelligent services and innovative solutions to urban problems.
• Predicting traffic crash severity using hybrid of balanced bagging classification and light gradient boosting machine
  1 Jan 2023 1 repository listed
  Accident severity prediction is a hot topic of research aimed at ensuring road safety as well as taking precautionary measures for anticipated future road crashes.
• MTCSNN: Multi-task Clinical Siamese Neural Network for Diabetic Retinopathy Severity Prediction
  14 Aug 2022 1 repository listed
  The novelty of this project is to utilize the ordinal information among labels and add a new regression task, which can help the model learn more discriminative feature embedding for fine-grained classification tasks.
• MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity Prediction
  25 Jul 2022 1 repository listed
  We respond to the national Pediatric COVID-19 data challenge with a novel machine learning model, MedML.
• Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift
  2 Jul 2022 1 repository listed
  In this paper, we propose the first method to tackle label shift for medical image classification, which effectively adapt the model learned from a single training label distribution to arbitrary unknown test label…
• COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings
  30 Jun 2022 1 repository listed
  We introduce a neural network for the prediction of the severity of lung damage and the detection of a COVID-infection using three-dimensional CT-data.
• GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity Estimation
  30 Jun 2022 1 repository listed
  Because of this clinical data scarcity and inspired by the recent advances in self-supervised large-scale language models like GPT-3, we use human motion forecasting as an effective self-supervised pre-training task for…
• The Severity Prediction of The Binary And Multi-Class Cardiovascular Disease -- A Machine Learning-Based Fusion Approach
  9 Mar 2022 1 repository listed
  To improve the performance of classification, a weighted score fusion approach was taken.
• A novel stacking framework based on hybrid of gradient boosting-adaptive boosting-multilayer perceptron for crash injury severity prediction and analysis
  17 Dec 2021 1 repository listed
  Crash injury severity prediction is a promising area of interest in traffic safety and management.
• Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction
  22 Nov 2021 1 repository listed
  In this context, we analyze the burned area severity estimation problem by exploiting a state-of-the-art deep learning framework.
• A Comparative Study on Machine Learning-based Approaches for Improving Traffic Accident Severity Prediction
  2 Nov 2021 1 repository listed
  The main purpose of this research is to employ machine learning-based approaches to predict crash injury severity and analyze the most influential factors contributing to road crashes as well as giving recommendations…
• Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data
  10 Sep 2021 1 repository listed
  We explore one of the most recent techniques called symbolic metamodeling to find the mathematical expression of the machine learning models for COVID-19.
• An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound
  1 May 2021 1 repository listed
  The proposed convolutional neural network (CNN) architecture implements an autoencoder network and separable convolutional branches fused with a modified DenseNet-201 network to build a vigorous, noise-free…
• COVIDX: Computer-aided diagnosis of Covid-19 and its severity prediction with raw digital chest X-ray images
  25 Dec 2020 1 repository listed
  In the absence of specific drugs or vaccines for the treatment of COVID-19 and the limitation of prevailing diagnostic techniques, there is a requirement for some alternate automatic screening systems that can be used…
• Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia
  3 Oct 2020 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  Reliability in Neural Networks (NNs) is crucial in safety-critical applications like healthcare, and uncertainty estimation is a widely researched method to highlight the confidence of NNs in deployment.
• AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab Posts
  30 Sep 2020 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate speech, offensive language, sexist and…
• Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task
  30 Sep 2020 1 repository listed
  The black-box nature of machine learning models hinders the deployment of some high-accuracy models in medical diagnosis.
• Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait
  25 Oct 2019 1 repository listed
  To our knowledge, this is the state-of-the-start performance in Parkinson's gait recognition.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.