Artificial intelligence (AI)

in medicine

Artificial Intelligence (AI) is one of the most popular areas of computer science and engineering. AI tries to reproduce what the human brain does. This means analysing, understanding, responding, learning and finding solutions. Since it is the computer that performs this reproduction, it is software that provides this intelligence. This intelligent software has the ability to find standalone solutions through big data analysis, to provide speech recognition, translate languages, manage mail, improve computer games, or analyse the behaviour of online browsers for customer-specific marketing. Banks use AI to predict changes in exchange rates or stock market movements, the automotive industry is working to use AI in autonomous cars that will drive without drivers, smartphones use AI to recognise faces, voices, etc. Superintelligence options are discussed, as well as AI risks. Big players like Google, Amazon, Baidu, Microsoft are investing billions in AI and their labour market is growing at high speed [1].


Health is not outside this “game” and AI is expected to have a massive impact on the currently established methods and therapeutic practices. This applies to diagnostics, medical therapy, new drug development, personalised treatment and overall health and prevention management, including gene editing [2].


How can computers learn?
Machine learning – algorithms can learn to find connections and manifestations related to diseases similarly to the way a doctor sees them. It is crucial for a computer to have as many specific examples as possible – several hundreds of thousands to millions of pieces of data to learn from. And, of course, this information must be digitised in order for the computer software to process it. So machine learning is particularly helpful in areas where diagnostic information is already digitised [3].


However, big data brings with it a new problem, and that is the speed of processing due to  the large volume. We are talking about quantum computers that are so intelligent that they can find the information they want immediately at the moment of measurement. Quantum computers are changing the paradigm of contemporary computer science and are giving us a new level of understanding of reality.


Today’s computers use bits—a stream of electrical or optical pulses representing 1s or 0s. Everything from your tweets and emails to your iTunes songs and YouTube videos are essentially long strings of these binary digits.


Quantum computers, on the other hand, use qubits, which are typically subatomic particles such as electrons or photons. Generating and managing qubits is a scientific and engineering challenge. Qubits have some quirky quantum properties that mean a connected group of them can provide much more processing power than the same number of binary bits. One of those properties is known as superposition and another is called entanglement.

What is superposition?

Qubits can represent numerous possible combinations of 1 and 0 at the same time. This ability to simultaneously be in multiple states is called superposition. To put qubits into superposition, researchers manipulate them using precision lasers or microwave beams. Thanks to this counterintuitive phenomenon, a quantum computer with several qubits in superposition can crunch through a vast number of potential outcomes simultaneously. The final result of a calculation emerges only once the qubits are measured, which immediately causes their quantum state to “collapse” to either 1 or 0.

What is entanglement?

Researchers can generate pairs of qubits that are “entangled,” which means the two members of a pair exist in a single quantum state. Changing the state of one of the qubits will instantaneously change the state of the other one in a predictable way. This happens even if they are separated by very long distances.


Nobody really knows quite how or why entanglement works. It even baffled Einstein, who famously described it as “spooky action at a distance”. But it’s key to the power of quantum computers. In a conventional computer, doubling the number of bits doubles its processing power. But thanks to entanglement, adding extra qubits to a quantum machine produces an exponential increase in its number-crunching ability. Quantum computers harness entangled qubits in a kind of quantum daisy chain to work their magic. The machines’ ability to speed up calculations using specially designed quantum algorithms is why there’s so much buzz about their potential.


Phenomena such as quantum tunnelling and quantum coherence are now widely accepted as being involved in vitally important processes for all living cells.


What remains indisputable is that the quantum dynamics that are undoubtedly taking place within living systems have been subject to 3.5 billion years of optimising evolution. It is likely that, in that time, life has learned to manipulate quantum systems to its advantage in ways that we do not yet fully understand.

In recent years, experimental measurements have uncovered fine quantum effects (FQE) in biological systems [2].


There is growing evidence that a number of specific mechanisms within living cells make use of the non-trivial features of quantum mechanics, such as long-lived quantum coherence, superposition, quantum tunnelling and even quantum entanglement—phenomena that were previously thought to be relevant mostly at the level of isolated molecular, atomic and subatomic systems, or at temperatures near absolute zero, and were thereby not thought to be relevant to the mechanisms responsible for life [3].


One of the most celebrated examples of the non-trivial role that quantum mechanics might be playing in biology is the claimed long-lived quantum coherence observed in the transport of exciton energy in photosynthesis. While this subject remains controversial, a more established role for quantum mechanics is found in the tunnelling of electrons and protons in enzyme catalysis . Beyond these examples of quantum biology, quantum entanglement has been implicated in avian navigation, while quantum tunnelling has been proposed to be involved in olfaction and mutation. More speculatively, some have suggested a link between quantum coherence and consciousness, although this view has little support within the neurobiology community [3].


The past few years have seen a rapidly growing interest among an expanding group of theoretical quantum physicists and chemists, experimental biochemists and spectroscopists who are carrying out serious theoretical and experimental studies of quantum effects in biology [3].


One of them is a prominent expert in the field of spectroscopy and quantum biology and inventor of a new medical technology called “ERI-Analytical Cloud system (AI)“ – Dr. Igor Orzhelskyi.

ERI – leverages the principles of quantum mechanics in biological systems

The ERI Analytical cloud system (AI) combines methods of emission spectroscopy, artificial intelligence and quantum mechanics.


Dr. I. Orzhelskyi, the inventor of ERI, describes the mechanism of quantum informatics in living systems in his book Theoretical foundation of physical and mathematical medicine:


“Take note that the brain is also in accordance with the principle of ‘non-locality’. Detecting the effect of non-local interactions of biological quantum systems is a prerequisite for maintaining a high degree of coherence (synchronisation) between the particles of the systems – atoms, molecules, cells, etc. Such unified cooperation can be achieved between the same type of cells and molecules, called enantiomers (cells created in one organ). This synchronisation serves as a medium for keeping the information“[3].


Figuratively, we can imagine these cells as a group of dancers, who are synchronously dancing the same dance. We can get information about the dance only when the dancers are in synchronicity. If each dancer is dancing differently, this group formation will not provide any information about the dance.


Information is an inseparable part of living systems.


Each living system is made up of three levels that form the basis of all living organisms: MATTER, ENERGY and INFORMATION. Matter is represented by particles having a double character as a particle and wave. Energy is manifested as waves depending on gravity. Information on a given system is kept in the synchronised oscillation (coherence) of the given cell cluster.


Twenty years of Dr. Orzhelskyi’s research confirms that in the normal/physiological condition of biological tissues and organs, a relative synchronicity between the structures that create these biological systems is observed. Conversely, in the presence of pathology or a condition that precedes pathology, this synchronous connection between the cells is interrupted.


Revealing this quantum information model of living systems based on coherency (oscillation) as an inevitable condition to preserve information based on non-locality and entanglement creates the platform of the ERI Analytical cloud system (AI).


The ERI (AI) software knows exactly how a particular organ/system should look when it is healthy and how it is in reality (see ERI General Principles below). If an organ is not broadcasting the right signal, the ERI software generates a correcting signal (emitted by a sensor/antenna) which interferes with the location of the pathology. As was mentioned, pathology is represented by a disruption of the synchronous connection (non-locality) and thus the system is losing information about healthy functionality from the system.

The technical implementation of the ERI regulatory signal leverages this quantum nature of living systems. The regulatory signal is primarily aimed at restoring the non-local connections in the individual quantum systems of the body by restoring their coherent (synchronous) state, thereby recovering the information, communication and regulatory processes between the structural elements within the systems and, in consequence, between other systems.


The ERI technology thus represents the first targeted intervention into the quantum level of cell communication and informatics to restore their non-locality (synchronicity) which is carrying precious information about their physiological state.


  1. MIT Technology review, Computing, quantum computing, Jan 29, 2019
  2. Measurement and prediction of quantum coherence effects in biological processes
    17 Sep 2015, Phys. Chem. Chem. Phys., 17 Sep 2015, 2015,17, 30772-30774
  3. Johnjoe McFadden: The Origin of quantum biology, DecDec 12, 2018
  4. Dr. I. Orzhelskyi, Theoretical foundation of physical and mathematical medicine“, 2006, ISBN 978-5-9906691-3-0
  5. Artificial Intelligence in Medicine,
  6. HIMSS INSIGHT 7.2, Dec.2018, Artificial Intelligence Dec 2018, 7.2,
  7. MAI / Master in Artificial Intelligence e_iZyUdrPdW-ph6nbNYtl3Upf7NrT8tOJTTBvUt0Oe2JFBBt4QHgn_RoC-dkQAvD_BwE

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