Changing how doctors diagnose diseases with AI | Microsoft Azure and NVIDIA

Healthcare Challenges & Opportunities - Healthcare data overload exceeds human capacity, hindering effective diagnosis and treatment [1] - Delayed or missed diagnoses, particularly in women's health, lead to prolonged suffering and uncertainty [2][3][4] - In women's health, for every one woman diagnosed, four remain undiagnosed or undertreated [5] - Up to 90% of patients are left untreated or undertreated despite available data [5] - Over half of patients with COPD remain undiagnosed or undertreated [10] - Significant variation in healthcare availability exists [20] Pangaea Data's Solution: PALLUX AI Platform - PALLUX mimics physician decision-making by integrating medical knowledge and patient interaction data [8][9] - PALLUX interprets patient data using clinical guidelines to provide real-time responses to clinicians [14][15] - PALLUX connects with different healthcare systems through various interfaces [15] - PALLUX, deployed with the NHS, found six times more undiagnosed cancer cachexia patients compared to traditional methods [19][20] - Early diagnosis via PALLUX can cut cachexia treatment costs by up to 50% and potentially save 1 billion pounds per year [20] - PALLUX helps find more patients who are falling in care gaps and bring them back on to the relevant care pathway [32] Technology & Collaboration - NVIDIA and Microsoft support Pangaea Data with AI technologies, including large language models and NVIDIA GPUs [16][24][25] - NVIDIA FLARE helps train centralized models while preserving patient privacy [24] - Microsoft Azure provides a compliant environment across different countries and territories [22][23] Impact & Future - Early diagnosis and guideline-concordant therapy improve patient outcomes and reduce hospital admissions [16][17] - AI-powered clinicians can provide more empathetic and personalized care [18] - Unlocking health record data can revolutionize the healthcare landscape [19] - Pangaea Data's approach can be applied globally to address challenges in identifying and treating patients [26]