Pattern Recognition System for Focal Liver Lesions Using “Crisp” and “Fuzzy” Classifiers

Hm, Klein; Eisele, Thomas P.; Kc, Klose; Stauss, I; Brenner, Mark; Ameling, Walter; Rw, Günther

doi:10.1097/00004424-199601000-00002

Cited by 6 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They have also been used to characterize MRI scans of brain tumors, 38 ultrasound scans of liver lesions, 39 and CT scans of breasts, 40,41 Fuzzy logic has also been used to predict the survival rates of breast cancer patients. 42 Using the principles of genetic algorithms, the outcomes of lung cancer, 43 melanoma, 44 and the reaction to warfarin 45 have all been predicted.…”

Section: Ai In Cancermentioning

confidence: 99%

Review on Artificial Intelligence in Medicine

Шарма¹,

Chaudhary²,

Mudgal³

et al. 2023

J Young Pharm.

View full text Add to dashboard Cite

Complex medical data can be extracted using artificial intelligence, a branch of computer science. Their capacity to identify meaningful relationships within a data set can be applied in a variety of therapeutic settings for outcome prediction, diagnosis, and treatment. Artificial intelligence in medicine is developing swiftly. Artificial intelligence-powered medical technology is fast becoming practical clinical practice-related solutions. The increasing amounts of data generated by mobile monitoring sensors found in wearables, smartphones, and other medical equipment can be handled by machine learning algorithms. The use of Artificial Intelligence (AI) in many medical professions is discussed in this illustrative article from the perspectives of seven distinct fields: machine learning, intelligent robotics, image recognition technology, expert systems, artificial neural networks, and evolutionary computation. Additionally, it covers AI's prospective and current applications in medicine.

show abstract

Section: Ai In Cancermentioning

confidence: 99%

Review on Artificial Intelligence in Medicine

Шарма¹,

Chaudhary²,

Mudgal³

et al. 2023

J Young Pharm.

View full text Add to dashboard Cite

show abstract

“…Similarly, the application of fuzzy logic has been explored in the diagnosis of acute leukaemia, 49 and breast 50 and pancreatic 51 cancer. They have also been applied to characterise ultrasound images of the breast, 52 ultrasound 53 and CT scan 54 images of liver lesions and MRI 55 images of brain tumours. Fuzzy logic has also been used to predict survival in patients with breast cancer.…”

Section: Fuzzy Expert Systemsmentioning

confidence: 99%

Artificial intelligence in medicine

Ramesh

Kambhampati²,

Monson³

et al. 2004

Ann R Coll Surg Engl

699

396

View full text Add to dashboard Cite

A rtificial intelligence (AI) is defined as 'a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behaviour, and with the creation of artefacts that exhibit such behaviour'.1 Aristotle attempted to formalise 'right thinking' (logic) through his syllogisms (a three part deductive reasoning). Much of the work in the modern era was inspired by this and the early studies on the operation of mind helped to establish contemporary logical thinking. Programs which enable computers to function in the ways, that make people seem intelligent are called artificial intelligent systems. The British mathematician Alan Turing (1950) was one of the founders of modern computer science and AI. He defined intelligent behaviour in a computer as the ability to achieve human-level performance in cognitive tasks, this later became popular as the 'Turing test'.2 Since the middle of the last century, researchers have explored the potential applications of intelligent techniques in every field of medicine.3,4 The application of AI technology in the field of surgery was first successively investigated by Gunn in 1976, when he explored the possibility of diagnosing acute abdominal pain with computer analysis. 5 The last two decades have seen a surge in the interest in medical AI.Modern medicine is faced with the challenge of acquiring, analysing and applying the large amount of knowledge necessary to solve complex clinical problems. The development of medical artificial intelligence has been related to the development of AI programs intended Artificial intelligence in medicine AN

show abstract

Prolegomena zu einer Wissenschaftstheorie der medizinischen Radiologie

Golder

2004

Der Radiologe

View full text Add to dashboard Cite

Pattern Recognition System for Focal Liver Lesions Using “Crisp” and “Fuzzy” Classifiers

Abstract: The system demonstrated a diagnostic accuracy comparable to human observers. Further improvement with increasing numbers of typical computed tomographic series for training of the classifier can be expected.

Cited by 6 publications

References 15 publications

Review on Artificial Intelligence in Medicine

Review on Artificial Intelligence in Medicine

Artificial intelligence in medicine

Prolegomena zu einer Wissenschaftstheorie der medizinischen Radiologie

Contact Info

Product

Resources

About