Medical Machinery.This chapter explores the evolutionary path geared toward medical machines (MMs) and their processors. Such machines deal with medical objects (such as patients, medical staff, drugs, and biological entities) and medical actions (such as treatment, surgeries, therapy, and counseling). Together they blend into very major macroscopic (humanist achievements, accomplishments, procedures, etc.) deeds in medicine or very minor (subsidiary, supporting, inconsequential, etc.) steps or functions in medical medical machinery.
The numerous steps of mechanization of the medical steps by numerous hardware units of machine hardware/firmware and/or of coordinated modules medicalware are streamlined in this chapter. The goal and the outcome are of prime importance. In the partitioning of such (medical) verb function on/by (medical) objects, computer science plays an unparalleled role. There are three such overlapping roles: first, the grouping (i.e., lexical analysis: classification of nouns and verbs); second, validating (i.e., syntactic analysis: validating the authenticity/legality of the desired verb on the appropriate noun), and third, contextual rendering (i.e., semantic analysis: validating the action of the verb on the noun in context to the medical goal that is to be achieved). The overall process is that of compilation a computer program. In this context, the medical compiler processes the request to the MM to accomplish a task or offer a series of steps to complete the task. The machine thus performs only valid task(s) for/by a valid operator(s) upon/for a valid noun object(s). Conversely, it also blocks illegal operation(s) associated with legal/illegal objects (syntactic check; verb → noun and noun ← verb) and prevents legal operations on illegal nouns (syntactic check; wrong verb → noun, verb → wrong noun, and wrong verb → wrong noun). Irrelevant operations to the overall task or out of context actions are flagged (semantic checks).
The science of medicine hinges on the knowledge. Knowledge like any other systematized information, inference, logic, and induction has its own rules for building new strings of knowledge or for concatenating old knowledge into new knowledge strings. The purpose of processing knowledge can be many fold, such as to evolve a series of steps toward a given goal (such as relieve a pain and perform a surgery), find the cause–effect relationship (such as cause and effect relation of a drug and the cause for inter-related ailments), and to find a cure. In handling such a routine, the MM stands to win as a computer can outperform a (an ordinary) human in game of chess or in arithmetic and logical functions.
In this chapter, we propose the seminal steps in medical machinery the discipline of computer science onto the science of medicine. Simple machines for simple tasks are addressed first and then the architectures of more complex MMs are proposed. The trajectory is through the domain of knowledge and through the realm of knowledge machines. In developing the origin of MMs from the origin of computers, the MMs become “certain” about what (how many, what sequence, what scientific basis) needs to be done upon/to and from what object(s) before the task is even started by the MM. This scenario is identical to the scenario that a compiler compiles before the execution of a program. In an interpreter-driven machine, the procedure is limited to single statement at a time. Interpreter-driven MMs may be inappropriate except for the simplest medical functions (such as prepare an operating room for surgery and prescribe a pain reliever) and even at that, for a human being to inspect every step each time the machine proposes a step. However, these tiniest steps proposed by the machine may be superior to those selected by humans because of the artificially intelligent (AI) rules (such as pattern recognition of verbs and objects and permissible actions for existing noun objects) embedded in the interpreter.
MMs that can function as sophisticated computers are rare. Even though medical facilities for magnetic resonance imaging (MRI) and for radiology use sophisticated computer systems for graphics and imaging, the availability of general-purpose medical computers is nonexistent. Functional complexity, network connectivity, emergency care, and patient privacy add to the medical information processing at the processor level, network switching and worldwide implementation of the AI techniques add to the features of the MM and its networking.
The design of successful machine-network cluster for the hospital, medical community centers, or even a small nation medical service provisioning facility can be challenging, yet a controlled evolutionary process. Like the space science of 60s has been a careful blend of physics, computer sciences, astronomy, and rocket technology, the medical processing and communication science can be (or has to be) a customized blend of medical knowledge, human discretion with its own unique decision support system, computer science, and communication technologies. Such extraordinary blending of scientific knowledge and human judgment occurs in activities of wise politician, great artists, and excellent musicians and even in some (very well) polished corporate executives.