{"total":43,"rows":[{"id":"2201.00382","title":"ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions","created":"2022-01-02","cited_by_count":153,"area":null},{"id":"2302.04062","title":"Machine Learning for Synthetic Data Generation: A Review","created":"2023-02-08","cited_by_count":120,"area":null},{"id":"2203.14500","title":"MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design","created":"2022-03-28","cited_by_count":66,"area":null},{"id":"2406.06316","title":"Tx-LLM: A Large Language Model for Therapeutics","created":"2024-06-10","cited_by_count":25,"area":null},{"id":"2305.12081","title":"MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement","created":"2023-05-20","cited_by_count":24,"area":null},{"id":"2404.01273","title":"TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model","created":"2024-04-01","cited_by_count":24,"area":null},{"id":"2409.04481","title":"Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials","created":"2024-09-06","cited_by_count":24,"area":null},{"id":"2401.03482","title":"Uncertainty Quantification on Clinical Trial Outcome Prediction","created":"2024-01-07","cited_by_count":19,"area":null},{"id":"2505.02874","title":"Uncertainty Quantification for Machine Learning in Healthcare: A Survey","created":"2025-05-04","cited_by_count":14,"area":null},{"id":"2304.05352","title":"SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning","created":"2023-04-07","cited_by_count":13,"area":null},{"id":"2306.04802","title":"A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises","created":"2023-06-07","cited_by_count":13,"area":null},{"id":"2506.04293","title":"AUTOCT: Automating Interpretable Clinical Trial Prediction with LLM Agents","created":"2025-06-04","cited_by_count":9,"area":null},{"id":"2404.13235","title":"TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction","created":"2024-04-20","cited_by_count":7,"area":null},{"id":"2406.03403","title":"Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?","created":"2024-06-04","cited_by_count":7,"area":null},{"id":"2406.10292","title":"Automatically Labeling Clinical Trial Outcomes: A Large-Scale Benchmark for Drug Development","created":"2024-06-13","cited_by_count":7,"area":null},{"id":"2407.02265","title":"DrugCLIP: Contrastive Drug-Disease Interaction For Drug Repurposing","created":"2024-07-02","cited_by_count":7,"area":null},{"id":"2209.09023","title":"Artificial Intelligence for In Silico Clinical Trials: A Review","created":"2022-09-16","cited_by_count":6,"area":null},{"id":"2305.19407","title":"FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection","created":"2023-05-30","cited_by_count":6,"area":null},{"id":"2407.00631","title":"TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets","created":"2024-06-30","cited_by_count":5,"area":null},{"id":"2210.02719","title":"Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks","created":"2022-10-06","cited_by_count":4,"area":null},{"id":"2303.11376","title":"GNN-Ensemble: Towards Random Decision Graph Neural Networks","created":"2023-03-20","cited_by_count":4,"area":null},{"id":"2407.13115","title":"TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models","created":"2024-07-18","cited_by_count":4,"area":null},{"id":"2411.00200","title":"MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets","created":"2024-10-31","cited_by_count":4,"area":null},{"id":"2306.04018","title":"PyTrial: Machine Learning Software and Benchmark for Clinical Trial Applications","created":"2023-06-06","cited_by_count":3,"area":null},{"id":"2306.11768","title":"Geometric Deep Learning for Structure-Based Drug Design: A Survey","created":"2023-06-20","cited_by_count":2,"area":null},{"id":"2408.10995","title":"CTP-LLM: Clinical Trial Phase Transition Prediction Using Large Language Models","created":"2024-08-20","cited_by_count":2,"area":null},{"id":"2604.16742","title":"CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction","created":"2026-04-17","cited_by_count":2,"area":null},{"id":"2405.06662","title":"Language Interaction Network for Clinical Trial Approval Estimation","created":"2024-04-26","cited_by_count":1,"area":null},{"id":"2405.08979","title":"drGT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network","created":"2024-05-14","cited_by_count":1,"area":null},{"id":"2501.06823","title":"MEXA-CTP: Mode Experts Cross-Attention for Clinical Trial Outcome Prediction","created":"2025-01-12","cited_by_count":1,"area":null},{"id":"2505.05577","title":"PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models","created":"2025-05-08","cited_by_count":1,"area":null},{"id":"2505.16097","title":"Developing Large Language Models for Clinical Research Using One Million Clinical Trials","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2505.24622","title":"Random Rule Forest (RRF): Interpretable and Manageable Ensembles of LLM-Generated Questions for Predicting Success from Unstructured Data","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2508.10899","title":"A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design","created":"2025-08-14","cited_by_count":1,"area":null},{"id":"2601.00290","title":"ClinicalReTrial: Clinical Trial Redesign with Self-Evolving Agents","created":"2026-01-01","cited_by_count":1,"area":null},{"id":"2409.07089","title":"TrialSynth: Generation of Synthetic Sequential Clinical Trial Data","created":"2024-09-11","cited_by_count":0,"area":null},{"id":"2411.17595","title":"Can artificial intelligence predict clinical trial outcomes?","created":"2024-11-26","cited_by_count":0,"area":null},{"id":"2505.18527","title":"CLaDMoP: Learning Transferrable Models from Successful Clinical Trials via LLMs","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2601.06300","title":"$\\texttt{AMEND++}$: Benchmarking Eligibility Criteria Amendments in Clinical Trials","created":"2026-01-09","cited_by_count":0,"area":null},{"id":"2603.29041","title":"A Latent Risk-Aware Machine Learning Approach for Predicting Operational Success in Clinical Trials based on TrialsBank","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2608.02688","title":"Learning Molecular Representations from Cellular Phenotypes with Structure Preservation","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.14598","title":"Position: Medical AI Neglects Real Treatment Outcomes","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2609.21859","title":"TrialAtlas: Multi-Agent Research Organization for Clinical Trial Design and Optimization","created":"2026-09-18","cited_by_count":0,"area":null}],"next_cursor":null}