How AI is revolutionising healthcare

by | 23 November 2021 | Basics

Would they have thought that 54 % of humanity is willing to put its trust in AI and robotics? This development in the consciousness of our society and the technical progress will have a lasting impact on the future of medicine. We want to provide comprehensive information about this process.

Faster, better diagnoses and drug development - opportunities for AI in the healthcare sector 

The increasing importance of artificial intelligence for research, diagnostics and therapy is based on the possibility of processing DNA sequences or diagnostic data with AI systems and drawing conclusions from them. Already today, there are platforms based on algorithms that can evaluate ECG signals, classify documents or make remote diagnoses.  

How can hospitals benefit from AI? 

Particularly large institutions in the healthcare sector can be supported and in some cases already guided in their work by the use of artificial intelligence - some examples of this would be: 

1. communication of doctors and patients from a distance:  

Implants and wearables already transmit information to health apps. This means that vital values are constantly monitored. In this way, diagnoses and prescriptions are made available without media disruptions or delays.  

2. bots for the diagnosis of diseases: 

The use of automated programmes significantly supports health professionals because the efficiency of e-histories using databases on typical diseases is already very high. 

3. AI-based evaluation of cardiac MRIs: 

The evaluation of tomography scans is a time-consuming and error-prone procedure. If it is performed manually or semi-automatically, the results depend on the individual experience of the healthcare professional. With the help of AI, the evaluation can be made more objective. 

Opportunities in drug research 

Artificial intelligences offer wide-ranging opportunities to accelerate progress and address ethical issues - already promising examples include: 

1. the use of 3D models: 

The use of a "digital twin" is already a reality for individual organs: 3D models of individual hearts are used for diagnosis and surgery preparation. The health of the real test person thus does not have to be risked or compromised. 

2. supercomputers for the analysis of drugs: 

Using a supercomputer, a team from the University College of London studied 50 drugs and potential drugs and their interaction with proteins in the human body. Machine learning was also used to test what effects the substances might have on disease treatments.  

And where is the humanity? - Risks of artificial intelligence in health care

Artificial intelligence requires very high computing power. Especially with the introduction of programmes that work with huge Data volumes To make it work, supervised training of the artificial intelligence is necessary.  

According to Ärzteblatt.de patient representatives named incorrect or discriminatory treatment decisions as one of their greatest fears. There is concern that medical staff will make adverse decisions for patients based on IT results.  
 
The possible risks for the quality of care through the use of AI technologies are also viewed critically. For example, due to cost-saving constraints in health care facilities, human interaction could be restricted in favour of highly standardised treatments. This naturally raises various ethical questions.  

The biggest social concern: data protection 

 Sensitive health data places increased demands on data security and data protection. Accordingly, new medical technologies can optimise patient care, but they increasingly offer attack surfaces for cybercrime. The healthcare sector is already one of the industries most frequently affected by cyber attacks. Security administrators in this sector are faced with the difficult task of not being allowed to hinder network processes with security measures and frequent, complex updates. But without suitable security solutions, entire healthcare facilities are quickly at risk.  

Success factors for AI in the healthcare sector 

In addition to various concerns, however, it is important to emphasise that the opportunities for more efficient and better care, as well as research, outweigh the risks. In order for our society to benefit as much as possible, specific issues need to be addressed:

Realise economic benefits

Artificial intelligence can lead to increased productivity and cost savings worldwide. The benefits for healthcare are highly variable and range from early detection of dementia, to individualised therapies for breast cancer, to early risk calculations for childhood obesity. 

Dialogue with the public

For the successful application of AI in healthcare, societal components must not be left out. According to a recent PWC study only about half of those with health insurance can currently imagine having robotic surgery or using artificial intelligence in general for their recovery.  

Anchoring artificial intelligence in the corporate culture 

People first have to get used to new developments in order to identify with them. For this, comprehensive information and training should be provided internally. 

Artificial intelligence is the key technology for the health sector

Machine learning has already been part of our healthcare system for a number of years, yet it can be assumed that the technologies used so far are only a small part of the possible deployment options in the future. Our Whitepaper AI in Medicine offers a deeper insight into the possibilities and success factors.  

We want to take a closer look at the risks, advances and opportunities of AI in the health sector, because information remains the key to the future. 

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Our AT editorial team consists of various employees who prepare the corresponding blog articles with the greatest care and to the best of their knowledge and belief. Our experts from the respective fields regularly provide you with current contributions from the data science and AI sector. We hope you enjoy reading.

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