Cover Image

A Novel Recurrent Neural Network Framework for Prediction and Treatment of Oncogenic Mutation Progression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Parthasarathy, Rishab, Bhowmik, Achintya
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation and Language Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Integrating Single-Cell Foundation Models with Graph Neural Networks for Drug Response Prediction
by: Rossner, Till, et al.
Published: (2025)

Predicting Side Effect of Drug Molecules using Recurrent Neural Networks
by: Beaudoin, Collin, et al.
Published: (2023)

Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations
by: Qi, Cong, et al.
Published: (2025)

Statistical NLP for Optimization of Clinical Trial Success Prediction in Pharmaceutical R&D
by: Doane, Michael R.
Published: (2025)

Rep3Net: An Approach Exploiting Multimodal Representation for Molecular Bioactivity Prediction
by: Islam, Sabrina, et al.
Published: (2025)

Tabular LLMs for Interpretable Few-Shot Alzheimer's Disease Prediction with Multimodal Biomedical Data
by: Kearney, Sophie, et al.
Published: (2026)

A Hybrid Machine Learning Model for Classifying Gene Mutations in Cancer using LSTM, BiLSTM, CNN, GRU, and GloVe
by: Aburass, Sanad, et al.
Published: (2023)

Integrating Biological-Informed Recurrent Neural Networks for Glucose-Insulin Dynamics Modeling
by: De Carli, Stefano, et al.
Published: (2025)

A Systematic Review on the Generative AI Applications in Human Medical Genomics
by: Changalidis, Anton, et al.
Published: (2025)

Handwriting Anomalies and Learning Disabilities through Recurrent Neural Networks and Geometric Pattern Analysis
by: Alevizos, Vasileios, et al.
Published: (2024)

Enabling Few-Shot Alzheimer's Disease Diagnosis on Biomarker Data with Tabular LLMs
by: Kearney, Sophie, et al.
Published: (2025)

VenusX: Unlocking Fine-Grained Functional Understanding of Proteins
by: Tan, Yang, et al.
Published: (2025)

HIGHT: Hierarchical Graph Tokenization for Molecule-Language Alignment
by: Chen, Yongqiang, et al.
Published: (2024)

Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries
by: Zhou, Liqi, et al.
Published: (2026)

Impact of automatic speech recognition quality on Alzheimer's disease detection from spontaneous speech: a reproducible benchmark study with lexical modeling and statistical validation
by: Samanta, Himadri S
Published: (2026)

Transformers for molecular property prediction: Lessons learned from the past five years
by: Sultan, Afnan, et al.
Published: (2024)

Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers Across Diseases
by: Yang, Yumeng, et al.
Published: (2024)

MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
by: Li, Jiatong, et al.
Published: (2024)

Geometric Stability: The Missing Axis of Representations
by: Raju, Prashant C.
Published: (2026)

MolBind: Multimodal Alignment of Language, Molecules, and Proteins
by: Xiao, Teng, et al.
Published: (2024)

Prot2Text: Multimodal Protein's Function Generation with GNNs and Transformers
by: Abdine, Hadi, et al.
Published: (2023)

Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing
by: Liu, Shengchao, et al.
Published: (2022)

Question Rephrasing for Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks
by: Chen, Zizhang, et al.
Published: (2024)

MUDI: A Multimodal Biomedical Dataset for Understanding Pharmacodynamic Drug-Drug Interactions
by: Ngo, Tung-Lam, et al.
Published: (2025)

GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data
by: Margeloiu, Andrei, et al.
Published: (2022)

CPE-Pro: A Structure-Sensitive Deep Learning Method for Protein Representation and Origin Evaluation
by: Gou, Wenrui, et al.
Published: (2024)

Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks
by: KC, Kishan, et al.
Published: (2022)

SGAC: A Graph Neural Network Framework for Imbalanced and Structure-Aware AMP Classification
by: Wang, Yingxu, et al.
Published: (2024)

KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Prediction
by: Li, Longlong, et al.
Published: (2024)

A Framework for Feature Discovery in Intracranial Pressure Monitoring Data Using Neural Network Attention
by: Socha, Jonathan D., et al.
Published: (2026)

Revolutionizing Personalized Cancer Vaccines with NEO: Novel Epitope Optimization Using an Aggregated Feed Forward and Recurrent Neural Network with LSTM Architecture
by: Basava, Nishanth
Published: (2024)

TriFit: Trimodal Fusion with Protein Dynamics for Mutation Fitness Prediction
by: Cho, Seungik
Published: (2026)

A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling
by: He, Tiantian, et al.
Published: (2025)

Large Language Model-informed ECG Dual Attention Network for Heart Failure Risk Prediction
by: Chen, Chen, et al.
Published: (2024)

Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers
by: Chen, Xuexin, et al.
Published: (2025)

PUMA: Discovery of Protein Units via Mutation-Aware Merging
by: Suyunu, Burak, et al.
Published: (2025)

Boosted Random Forests for Predicting Treatment Failure of Chemotherapy Regimens
by: Shahid, Muhammad Usamah, et al.
Published: (2025)

MC-NN: An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types
by: Xu, Yanhua, et al.
Published: (2023)

DDoS: A Graph Neural Network based Drug Synergy Prediction Algorithm
by: Schwarz, Kyriakos, et al.
Published: (2022)

DrugAssist: A Large Language Model for Molecule Optimization
by: Ye, Geyan, et al.
Published: (2023)