This paper presents a scalable deep learning pipeline hosted on cloud platforms to process wearable sensor data. The system identifies cardiovascular anomalies using real-time signals, aiding early diagnosis and enabling continuous remote monitoring for patients at risk of heart-related medical conditions.

Julian Robert Fairchild, Harriet Eleanor Beckett, Theodore James Whitmore, Felicity Anne Middleton, Louis Alexander Carmichael

This study proposes a privacy-preserving classification framework using transformer models integrated with differential privacy techniques. Hosted in the cloud, the framework ensures compliance with medical data privacy laws while maintaining robust accuracy across distributed electronic health record systems.

Arthur Benjamin Wycliffe, Cecilia Florence Hayworth, Henry Samuel Blackstone, Florence Matilda Cunningham, Edwin George Rutherford

This work introduces a scalable knowledge graph system hosted on cloud infrastructure for mining insights from biomedical literature. The framework integrates NLP and graph databases to identify emerging patterns and supports automated literature-based discovery for disease treatment and drug repurposing efforts.

Samuel Lewis Kingsley, Alice Georgina Bright, Tristan Harold Edmonds, Charlotte Mayworth Poole, Benjamin Oscar Redgrave

We introduce a decision support framework that analyzes temporal clinical indicators to predict patient deterioration. Built on scalable cloud systems, the model enables proactive interventions by healthcare professionals, offering real-time risk scoring and alert generation through continuous patient data analysis.

Gregory Charles Denton, Amelia Rosalind Talbot, Victor Thomas Bexley, Sophia Eliza Bradford, Hugo Elliot Montrose

This study introduces a multilingual named entity recognition (NER) framework optimized for clinical documents. Hosted on cloud platforms, it uses contextual embeddings for improved accuracy across different languages and enhances information retrieval in international health record systems and biomedical research repositories.

Isidore Malcolm Trenchard, Annabelle Rose Whitworth, Laurence Philip Goodwin, Rosalind Beatrice Crawford, Matthew Graham Pennington

This research proposes a predictive analytics framework for personalized oncology treatment. Utilizing federated genomic data and hosted on secure cloud platforms, the model enables collaborative learning across institutions without data sharing, improving cancer treatment precision while ensuring patient privacy and data sovereignty.

Leonard Maxwell Griffin, Victoria Elise Hammond, Sebastian Arthur Bloomfield, Clarissa Madeleine Weller, Frederick Henry Dalrymple

This paper explores the use of cloud-based deep feature extraction for mental health prediction. By analyzing voice, text, and facial expression data from patient interactions, the system provides clinicians with emotional indicators and behavioral insights for early-stage intervention and support planning.

Gareth Franklin Lovett, Helena Violet Cresswell, Dominic Alfred Pemberton, Penelope Jane Hartford, Oliver Nathaniel Yorke