Digital Health Intelligence Market Analysis: AI in Clinical Imaging – shaping the future of healthcare

In a new series of Digital Health Intelligence Market Analysis, HealthTech Founder and M&A Advisor Lloyd Price examines a range of high potential market segments in the UK, including:

1. Virtual Care – From Hype to Reality

2. Patient Engagement Platforms – Rebuilding Trust in the NHS

3. Population Health – from Reactive Care to Proactive Prevention

4. Digital Therapeutics – looking forward to a year of growth

5. AI in Clinical Imaging – shaping the future of healthcare

Digital Health Intelligence Market Analysis - from identifying high value market segments to sales prospecting, Intelligence supports multiple teams with essential insights and reliable, granular-level data on NHS acute and mental health trusts, central bodies, STPs, ICSs and commissioning organisations.

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1. DHI Market Analysis: Virtual Care – From Hype to Reality

In the first of a new series of analyses for Digital Health Intelligence subscribers, Lloyd Price examines the virtual care market.

Virtual care holds potential in healthcare delivery, blending innovation with tradition. However, beneath the surface lies complexity. NHS frontline staff, navigating post-COVID challenges, perceive virtual wards as additional digital tasks, amid staffing shortages and mounting hurdles.

2. DHI Market Analysis: Patient Engagement Platforms – Rebuilding Trust in the NHS

Patient engagement platforms are gaining momentum with NHS England’s backing. They’re central to the ‘Digital Front Door’ strategy, focusing on patient-facing services, enhancing secondary care, and reducing the strain on frontline services. These platforms address the pandemic-induced disconnect between patients and the NHS.

3. DHI Market Analysis: Population Health – from Reactive Care to Proactive Prevention

This report offers a comprehensive overview of the evolving landscape of population health management and the challenges and opportunities it presents to the NHS. It underscores the importance of proactive approaches to healthcare and the critical role that data and technology will play in shaping the future of healthcare in the UK.

4. DHI Market Analysis: Digital Therapeutics – looking forward to a year of growth

The Digital Health Intelligence (DHI) Market Analysis on Digital Therapeutics highlights the transformative impact of evidence-based interventions delivered through devices. In the past year, there has been a significant surge in the adoption of digital therapeutics, especially within the NHS, addressing various healthcare challenges.

5. AI in Clinical Imaging – shaping the future of healthcare

Our analysis of AI in Clinical Imaging reveals a significant NHS commitment to leveraging artificial intelligence for improved patient care. The NHS AI Lab, regional networks, and funding initiatives showcase strategic investments in cutting-edge technology. Real-world examples from leading healthcare providers highlight AI’s tangible benefits, while acknowledging challenges such as data quality and ethical considerations.

Looking ahead, the report anticipates AI’s continued impact on disease detection and patient outcomes, underscoring its promising role in reshaping clinical imaging practices.

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AI in Clinical Imaging – shaping the future of healthcare

The NHS is proactively embracing artificial intelligence to enhance clinical imaging on the frontlines, from assisting radiologists in interpreting scans to automating tasks such as image segmentation and analysis.

Recognising the potential to positively impact clinical workflows and improve patient outcomes at a national level, the NHS Transformation Directorate set up the NHS Artificial Intelligence Laboratory (NHS AI Lab) in August 2019.

The NHS AI Lab is a collaboration between the government, NHS providers, academics and technology companies with a mission to develop and deploy AI technologies to improve the quality and efficiency of health and care services. The lab is focused on rigorous research, collaboration and innovation to ensure that AI is used effectively and safely to improve patient care.

In the last few years, AI has been widely adopted across the NHS, transforming clinical imaging and revolutionising disease detection, diagnosis and treatment. As AI continues to develop and evolve, its role in clinical imaging is expected to become even more significant, shaping the future of healthcare.

One of the biggest drivers of adoption has been at a regional level, directly resulting from the NHS's investment in regional clinical imaging AI networks such as East Midlands Imaging Network, Thames Valley Radiology Network and Yorkshire Imaging Collaborative.

AI in Clinical Imaging – One year from now

Artificial intelligence is expected to play an increasingly important role in clinical imaging in the years to come. Artificial intelligence algorithms are becoming more sophisticated and accurate, and the NHS is continuing to invest in their development and deployment. As a result, we should see even more innovative uses of AI in clinical imaging in the future, which will help to improve patient care and outcomes.

We can expect to see an increase in the use of AI in clinical imaging in three main clinical areas throughout the NHS in 2024:

1. Lung cancer detection: AI algorithms to analyse chest X-rays and CT scans for the early detection of lung cancer, one of the leading causes of cancer-related deaths in the UK. These AI-powered tools can identify subtle abnormalities that might be missed by human radiologists, enabling earlier intervention and improving patient outcomes.

2. Brain tumour segmentation: AI to segment brain tumours in MRI scans, accurately outlining the tumour’s boundaries and distinguishing it from surrounding healthy tissue. This precise segmentation aids in treatment planning, guiding neurosurgeons during surgery and facilitating radiation therapy targeting.

3. Stroke diagnosis and triage: AI algorithms to analyse CT scans and MRI scans of the brain to detect and classify strokes, enabling rapid diagnosis and triage of stroke patients. This timely intervention can significantly improve patient outcomes and reduce the risk of long-term disability.

In addition to the numerous clinical benefits, the biggest wins we are likely to see from AI in clinical imaging is for the workforce, specifically, reducing fatigue for radiologists and sharing clinical information across regional AI networks.

AI can help to reduce the heavy workload of radiologists by automating many tedious and time-consuming tasks, allowing them to focus on providing more accurate and timely diagnoses.

The NHS's investment in regional clinical imaging AI networks is a major step forward in the adoption of AI in healthcare. These networks have the potential to improve the accuracy, speed, and efficiency of patient care.

Overall, taking the challenges into consideration, the prospects for growth and development of AI in clinical imaging are strong, mainly because this is a particularly well-resourced area of AI tech with support from NHS trusts, senior managers and clinicians.

Digital Health Intelligence:

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