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How AI is changing the state of healthcare


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The use of artificial intelligence in the healthcare sector has already brought about positive changes such as cost reduction, improved consumer engagement and automated workflow. With the rapid growth of AI technology and the importance of tech transfer in the medical and pharmaceutical fields, it is expected that AI will become an indispensable part of giving and receiving healthcare in the near future.


Furthermore, the current pandemic has urged the sector to increase investment and leverage AI to help with clinical trials, drug discovery, remote patient care and delivering more efficient and timely diagnoses and treatments. In this article, we’ll take a look at four examples of how Artificial Intelligence is changing the state of healthcare.


AI-powered virtual health

Healthcare organisations were already investing in AI-assisted technology before the onset of the COVID-19 pandemic. In the United States, for instance, 75% of large organisations invested over $50 million in AI technologies, products and projects, while 95% of small to mid-sized organisations invested just under $50 million in 2019. Now, with the global spread of COVID-19 and the new challenges the healthcare industry is facing, there will be an increase in investment and a renewed focus on utilising AI solutions in healthcare. Paired with a robust data security plan and smart management, medical enterprises will certainly benefit in terms of cost reduction and efficient customer engagement with both the short- and long-term use of AI.


The pandemic has exposed the limitations of the healthcare system worldwide, including the lack of clinical staff and resources. According to an article published in Deloitte Insights, there has been ‘an unprecedented shift to virtual health, fueled by necessity and regulatory flexibility’ since March 2020. AI-powered, virtual health programmes can help with early diagnosis of various illnesses and reduce non-urgent admission and care.


Adopting omnichannel virtual care and integrating conversational AI in medical contact centres can certainly enhance customer experience while improving workflow and efficiency. AI will help automate repetitive tasks and reduce the cost of expensive operations. The digital front will help resolve administrative enquiries and redirect patients to appropriate endpoints of care. This will regulate the workload and avoid burnout among both admin and medical staff.


AI-assisted digital care can also help with triage and remote patient care by maintaining touchpoints with patients and flagging when they need care. By reducing the length of hospital stays and avoiding unnecessary visits, virtual healthcare plans allow for smart management of resources and workflow at centres.


In general, AI innovation leads to smart workforce management. Scheduling and planning staff rotation in healthcare centres has turned into a serious challenge since the pandemic. AI solutions assist with the speed, fluency and precision of organisational tasks by taking into consideration multiple operational constraints such as the number of staff, their availability and skill sets as well as the specific equipment required.


Medical diagnostics

Beyond remote patient care, AI-powered virtual assistants can aid in medical diagnostics and delivery of personalised and contextual care. Artificial intelligence analyses and interprets large amounts of data through complex algorithms and machine learning. Therefore, access to real-time, data-driven insights enables the clinical staff to make better decisions by modifying and implementing data based on their personal expertise.


AI innovation has the potential to deliver personalised solutions in complex medical cases while minimising the risk of erroneous diagnosis or medication errors that occur in traditional clinical decisions. Most recently, researchers at the Mount Sinai health system in New York City developed an AI algorithm to help with rapid detection of COVID-19 cases. Mimicking the physicians’ workflow, the algorithm processed data from patients’ chest CT scans, their medical history, current symptoms and even contact with possible sources of infection to provide a final diagnostic. According to a Mount Sinai press release, the AI-powered system detected 68% of positive COVID-19 cases who had gone undetected based on their negative CT scan appearance.


Patient identification

One of the most complicated procedures in the medical field is patient identification for the purpose of running successful clinical trials. Artificial intelligence has the ability to identify and assess data from massive data banks. Using machine learning, AI-integrated programmes identify and match patients into clinical trials based on their medical progress. The procedure is usually lengthier and more expensive without the use of smart technology.


Besides patient identification for clinical trials, new models of AI innovation can apply data to de-risk the process of drug discovery and improve the chance for success along the development cycle. In general, the use of AI and ML is associated with reducing long timelines and processes related to drug discovery and market distribution.


Increased cybersecurity and efficiency

As mentioned earlier, health plans and systems can use AI-augmented tech to gain insights and develop new products and services as well as improve their customer satisfaction rate. However, one of the main reasons decision-makers and clinicians deter further investment in AI innovation is closely tied to data theft and cybersecurity concerns. Nevertheless, it has been shown that leveraging the same technology, health centres can proactively detect and manage fraud, waste and abuse. This results in recovered payments and cost avoidance, saving them millions and improving patient care. Furthermore, future investment will lead to debugging the system and more efficient use of smart technology in the field.



Healthcare organisations can provide cognitive care-to-cure solutions by investing in and integrating artificial intelligence in their operations. AI-enabled care includes monitoring patients and their symptoms, delivering timely and efficient care (in person or virtually) and providing personalised service through the use of AI-assisted call centres, agents and voice analytics. On the other hand, an AI-driven workforce utilises AI-powered tools to optimise limited resources and talent allocation, hence improving efficiency, lowering costs and reducing burnout.


When it comes to diagnostics, AI’s capabilities to extract insights from data sets and to utilise machine learning give it a competitive edge in handling complex operations compared to human beings. AI-powered tools and programmes have the potential to recognise, monitor and categorise symptoms while detecting anomalies and predicting outcomes. This will enable healthcare specialists to provide holistic treatments based on data-driven decisions. Treatments will become more consumer-focused and prevention-oriented, and AI-embedded analytics will augment the medical staff’s decision-making acumen.



The Collider is a venture-building programme that works hard to bridge the gap between science, corporates and entrepreneurship. This innovation project encourages tech-transfer initiatives to connect science and entrepreneurial talent and create disruptive technology-based startups. The Collider is powered by Mobile World Capital Barcelona, a tech-focused initiative that aims to drive the digital transformation of society to help improve people’s lives globally.