Artificial intelligence (AI) is gradually changing medical practice. With recent progress in digitized data acquisition, machine learning and computing infrastructure, AI applications are expanding into areas that were previously thought to be only the province of human experts. In this Review Article, we outline recent breakthroughs in AI technologies and their biomedical applications, identify the challenges for further progress in medical AI systems, and summarize the economic, legal and social implications of AI in healthcare.

Artificial Intelligence in Healthcare

Objective:The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new deve

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Artificial Intelligence in Surgery: Promises and Perils

Survey paper: A survey on industrial applications of fuzzy control

A system includes a semiconductor device. The semiconductor device includes a first single crystal silicon layer comprising first transistors, first alignment marks, and at least one metal layer overlying the first single crystal silicon layer, wherein the at least one metal layer comprises copper or aluminum more than other materials; and a second single crystal silicon layer overlying the at least one metal layer. The second single crystal silicon layer comprises a plurality of second transistors arranged in substantially parallel bands. Each of a plurality of the bands comprises a portion of the second transistors along an axis in a repeating pattern.

System comprising a semiconductor device and structure

A device comprising semiconductor memories, the device comprising: a first layer and a second layer of layer-transferred mono-crystallized silicon, wherein the first layer comprises a first plurality of horizontally-oriented transistors; wherein the second layer comprises a second plurality of horizontally-oriented transistors; and wherein the second plurality of horizontally-oriented transistors overlays the first plurality of horizontally-oriented transistors.

Semiconductor device and structure

Background
Autonomous control of surgical robotic platforms may offer enhancements such as higher precision, intelligent manoeuvres, tissue-damage avoidance, etc. Autonomous robotic systems in surgery are largely at the experimental level. However, they have also reached clinical application.

Methods
A literature review pertaining to commercial medical systems which incorporate autonomous and semi-autonomous features, as well as experimental work involving automation of various surgical procedures, is presented. Results are drawn from major databases, excluding papers not experimentally implemented on real robots.

Results
Our search yielded several experimental and clinical applications, describing progress in autonomous surgical manoeuvres, ultrasound guidance, optical coherence tomography guidance, cochlear implantation, motion compensation, orthopaedic, neurological and radiosurgery robots.

Conclusion
Autonomous and semi-autonomous systems are beginning to emerge in various interventions, automating important steps of the operation. These systems are expected to become standard modality and revolutionize the face of surgery. Copyright © 2011 John Wiley & Sons, Ltd.

Evolution of autonomous and semi-autonomous robotic surgical systems: a review of the literature

Fuzzy logic controllers (FLCs) are finding increasing popularity in real industrial applications, especially when the available system models are inexact or unavailable. This paper proposes a zero-order Takagi---Sugeno parameterized digital FLC, processing only the active rules (rules that give a non-null contribution for a given input data set), at high frequency of operation, without significant increase in hardware complexity. To achieve this goal, an improved method of designing the fuzzy controller model is proposed that significantly reduces the time required to process the active rules and effectively increases the input data processing rate. The digital fuzzy logic controller discussed in this paper achieves an internal core processing speed of at least 200 MHz, featuring two 8-bit inputs and one 12-bit output, with up to seven trapezoidal shape membership functions per input and a rule base of up to 49 rules. The proposed architecture was implemented in a field programmable gate array chip with the use of a very high-speed integrated-circuits hardware description language and advanced synthesis and place and route tools.

Design and Implementation of a Fast Digital Fuzzy Logic Controller Using FPGA Technology

Fuzzy logic path tracking control for autonomous non-holonomic mobile robots: Design of System on a Chip

A low computational cost method is proposed for detecting actuator/sensor faults. Typical model-based fault detection (FD) units for multiple sensor faults require a bank of estimators [i.e., conventional Kalman estimators or artificial intelligence (AI)-based ones]. The proposed FD scheme uses an AI approach for developing of a low computational power FD unit abbreviated as $i$ FD. In contrast to the bank-of-estimators approach, the proposed $i$ FD unit employs a single estimator for multiple actuator/sensor FD. The efficacy of the proposed FD scheme is illustrated through a rigorous analysis of the results for a number of sensor fault scenarios on an electromagnetic suspension system.

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AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications

Genetic algorithm (GA) is a directed random search technique working on a population of solutions and is based on natural selection. However, its convergence to the optimum may be very slow for complex optimisation problems, especially when the GA is software-implemented, making it difficult to be used in real-time applications. In this article, a parameterised GA intellectual property core is designed and implemented on hardware, achieving impressive time-speedups when compared to its software version. The parameterisation stands for the number of population individuals and their bit resolution, the bit resolution of each individual's fitness, the number of elite genes in each generation, the crossover and mutation methods, the maximum number of generations, the mutation probability and its bit resolution. The proposed architecture is implemented in a field programmable gate array chip with the use of a very high-speed integrated-circuits hardware description language and advanced synthesis and place and...

Kyriakos M. Deliparaschos

Papers

Evolution of autonomous and semi-autonomous robotic surgical systems: a review of the literature

Design and Implementation of a Fast Digital Fuzzy Logic Controller Using FPGA Technology

Fuzzy logic path tracking control for autonomous non-holonomic mobile robots: Design of System on a Chip

AI-Based Actuator/Sensor Fault Detection With Low Computational Cost for Industrial Applications

A parameterised genetic algorithm IP core: FPGA design, implementation and performance evaluation