AI-driven 'Deep Medicine' Can Revolutionize Healthcare Within The NHS.

AI-driven 'Deep Medicine' Can Revolutionize Healthcare Within The NHS.
AI-driven 'Deep Medicine' Can Revolutionize Healthcare Within The NHS

Today’s NHS faces severe time constraints, with the risk of short consultations and concerns about the risk of misdiagnosis or delayed care. These challenges are compounded by limited resources and overstretched staff, which results in protracted patient wait times and generic treatment strategies.

Staff can operate with a surface-level view of patient data, relying on basic medical histories and recent test results. This lack of comprehensive data interferes with their ability to fully understand patient needs and compromises the accuracy of diagnoses and treatments.

The American cardiologist and scientist Eric Topol introduced the concept of “deep medicine” in his 2019 book,Deep Medicine: How Artificial Intelligence can make Healthcare human again. He critiques the US’s shallow medicine model and offers insights from his clinical and personal experiences.

Deep medicine holds the potential to revolutionize medical diagnostics, the effectiveness of treatments, and operational considerations. Topol presents artificial intelligence (AI) as the transformative solution to these systemic shallow issues. He outlines what he calls the deep medicine framework as a comprehensive strategy for the incorporation of AI Solutions in healthcare in different aspects.

The foundation of deep medicine rests on three main pillars: deep phenotyping, deep learning, and deep empathy. These pillars are closely linked, and embracing this framework has the potential to improve patient care, assist healthcare staff, and fortify the entire NHS system.

Deep phenotyping

Deep phenotyping refers to a comprehensive picture of an individual’s health data across a full lifetime. A deep phenotype goes far beyond the limited data collected during a standard medical appointment or health episode. It includes things such as a person’s genetic code, the entirety of an individual’s DNA, and information about the body’s microbes or microbiome.

It encompasses what’s known as the “exposome,” the things in the environment that a person is exposed to during life, such as air pollution. It includes markers that reveal details of the metabolic processes going on in a person’s body and the proteins their body is expressing, as well as other biological measures and metrics. It comprises a person’s electronic health records, including their medical history, diagnoses, treatments, and lab results.

Deep learning

The philosophy of deep phenotyping is to combine this diverse data to enable more accurate and speedy diagnoses to advance predictive and preventative medicine strategies. However, the sheer volume and complexity of the collected data pose significant challenges for analyzing it all. This is where deep learning — an area of AI Solutions that seeks to simulate the decision-making power of the human brain — is so valuable.

AI could potentially improve how diagnostic tools are used.

Deep empathy

Integrating AI Solutions can help manage operational tasks in health services like the NHS. These include management and hospital workflows. However, the development of AI Solutions should not be revised — rather, it need to be targeted at real clinical needs and designed to foster better relations between patients and staff. This is the pillar of deep medicine, known as deep empathy.

By bringing all these together, we're building a future where healthcare is both smart and kind. It's a world where doctors have the time and tools to connect with their patients, making healthcare better for everyone. So, as we step into this new era of 'deep medicine,' let's remember that caring for people isn't just about fixing bodies—it's about touching hearts too.

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Source-The Conversation