Quantum Computing and The Bloch Sphere
Quantum computing’s immense computing capability should allow clinicians to integrate a vast and disperse set of datasets to identify risk models, care treatment paths, and more. The ability to understand the impact of social-economic on an individual's health and not just a cohort may be within our reach. Providing consumers and patients with greater precision into their future healthcare state would be viable with quantum computing power.
See https://centricconsulting.com/blog/how-quantum-computing-will-impact-healthcare/
The Bloch sphere, https://en.wikipedia.org/wiki/Bloch_sphere , is a representation of a qubit, https://en.wikipedia.org/wiki/Qubit , the fundamental building block of quantum computers.
The following section on quantum computing, written by Matt Versaggi, did not make its way to the ebook, State of Healthcare Technology, but is included here. Do visit Matt's site for AI resources, http://www.matt-versaggi.com/mit_open_courseware/ .
Quantum Computing
Quantum computing promises to revolutionize computation and how fast — it represents an entirely new approach to the task of computing itself, using the strange, almost bizarre behaviors of subatomic particles as described by quantum mechanics. Quantum is more future technology than presently available technology for healthcare.
What It Is
The essence of quantum computing is to build a computer that uses the multi-state logic of quantum mechanics as its underlying circuitry instead of the binary logic used in today's computers. The two types of computing work very differently. Binary logic uses values of 1 and 0 (called bits) to store and process data, whereas quantum computing uses Qubits, values of 1 and 0, and everything in between.
The world of quantum mechanics operates at the level of subatomic particles, such as photons. At that microscopic scale, the universe's laws get very weird in ways that are difficult to understand, even for many physicists. For instance, in a phenomenon called entanglement, two photons with separate states can become entangled, and their different states fuse into a single shared state.
Another odd quantum phenomenon is superposition, in which a Qubit can simultaneously possess two or more values for an observable quantity. In other words, unlike a regular bit in today's computers, the Qubit could simultaneously be both one and zero.
Quantum computing appears promising when addressing the following types of difficult problems:
Computationally challenging problems: Problems solvable in polynomial computation time (as the size of the input grows, the processing time of the algorithm takes a lot longer)
Massive parallelism: Using superposition to perform 2n operations at the same time called quantum parallelism
Quantum simulators: The study of quantum systems that are difficult to study in the laboratory and impossible to model with a binary logic supercomputer
From the vacuum tube through solid-state transistors, the physical evolution of binary computational devices has produced mature binary computing circuitry to the modern integrated circuit. The relatively exotic superconducting circuits, trapped ions, optical traps, quantum dots, diamond vacancies, and semiconductor impurities of quantum computing are not evolved or mature. They are in their infancy, which is currently one of the biggest problems preventing quantum computing from progressing.
Quantum computing most likely be relegated to "co-processor" status within another computer, often referred to as a quantum processing unit (QPU).
This arrangement changes the way programmers will think about programming in the quantum computing world. For the most part, programs run on a classical computer, with only particular tasks sent to the QPU for processing. The result from the QPU goes back to the classical computer, and processing continues.
Quantum computing systems currently lack sufficient capacity, are highly fragile, and are mostly relegated to the laboratory. The material science and physics engineering community are working on ways to hold a subatomic particle long enough and well enough to do proper information processing.
As a result, commercially available quantum computing systems will not be available for several years.
How It Solves Healthcare Challenges
The strategic areas to apply quantum computing to healthcare are likely to be in the following areas:
Optimization
Computational speedup
Accuracy
Security
Simulation
Machine learning
Use Cases
The healthcare use cases of quantum computing are numerous. This section describes a few of them.
Improving MRI
A novel type of quantum-based MRI known as the bio-barcode assay, can now detect disease-specific biomarkers in blood using gold (and potentially diamond) nanoparticles. These are visible using MRI technology and have unique quantum properties that allow them to attach to disease-fighting cells. See https://www.fastcompany.com/3016530/4-ways-that-quantum-technology-could-transform-health-care.
Speeding up machine learning
Machine learning can leverage quantum parallelism for faster results. There is a growing trend toward applying machine learning to aid in diagnoses patient disease states. See https://blogs.bmj.com/technology/2017/11/03/quantum-computing-and-health-care/
Helping with radiation treatment
Radiation therapy is the most widely used form of cancer treatment. A quantum computer can run multiple richer simulations to arrive at an optimal solution.
Other possible uses
Quantum computing also holds promise in a wide variety of other healthcare applications, such as keeping sensitive data safe, speeding up human genome sequencing, creating simulations to speed up drug discovery, achieving better and faster protein folding, and advancing personalized medicine, and improving drug interaction through modeling complex molecular interactions at the atomic level.
Where It's Headed
In general, you can expect the following from quantum computing:
Solve its technical problems and evolve at the rate that its value to industry and government demands (much like defense technologies)
Provide spin-off industries, disrupt incumbent industries, and force significant change in mainstream industries, much like any significant emerging technology has done in the past.
Significantly impact healthcare because it is a rich, deep, broad, and complex problem with an abundance of potential applications.
May assist in the healthcare industry transformation from a fee for service model to a value-based care model. It may also undergird the creation of entirely new markets for healthcare products and services in a new value-based healthcare economy.