Literature DB >> 7964215

A proposed computer diagnostic system for malignant melanoma (CDSMM).

S Shao1, R R Grams.   

Abstract

This paper describes a computer diagnostic system for malignant melanoma. The diagnostic system is a rule base system based on image analyses and works under the PC windows environment. It consists of seven modules: I/O module, Patient/Clinic database, image processing module, classification module, rule base module and system control module. In the system, the image analyses are automatically carried out, and database management is efficient and fast. Both final clinic results and immediate results from various modules such as measured features, feature pictures and history records of the disease lesion can be presented on screen or printed out from each corresponding module or from the I/O module. The system can also work as a doctor's office-based tool to aid dermatologists with details not perceivable by the human eye. Since the system operates on a general purpose PC, it can be made portable if the I/O module is disconnected.

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Mesh:

Year:  1994        PMID: 7964215     DOI: 10.1007/BF00999454

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  2 in total

1.  How to build a computer-assisted, diagnosis-finding system. An example in dermatopathology.

Authors:  H Kolles; K Remberger
Journal:  Arch Pathol Lab Med       Date:  1991-10       Impact factor: 5.534

Review 2.  Malignant melanoma in the 1990s: the continued importance of early detection and the role of physician examination and self-examination of the skin.

Authors:  R J Friedman; D S Rigel; M K Silverman; A W Kopf; K A Vossaert
Journal:  CA Cancer J Clin       Date:  1991 Jul-Aug       Impact factor: 508.702

  2 in total
  9 in total

1.  Tutorial on technology transfer and survey design and data collection for measuring Internet and Intranet existence, usage, and impact (survey-2000) in acute care hospitals in the United States.

Authors:  M Hatcher
Journal:  J Med Syst       Date:  2001-02       Impact factor: 4.460

2.  Intranet usage and potential in acute care hospitals in the United States: survey-2000.

Authors:  M Hatcher
Journal:  J Med Syst       Date:  2001-12       Impact factor: 4.460

3.  Technology transfer with system analysis, design, decision making, and impact (Survey-2000) in acute care hospitals in the United States.

Authors:  M Hatcher
Journal:  J Med Syst       Date:  2001-10       Impact factor: 4.460

Review 4.  Information technology in the future of health care.

Authors:  Myron Hatcher; Irene Heetebry
Journal:  J Med Syst       Date:  2004-12       Impact factor: 4.460

5.  Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier.

Authors:  Qiang Li; Feng Li; Kunio Doi
Journal:  Acad Radiol       Date:  2008-02       Impact factor: 3.173

6.  Decision-making with and without information technology in acute care hospitals: survey in the United States.

Authors:  M Hatcher
Journal:  J Med Syst       Date:  1998-12       Impact factor: 4.460

7.  Novel Approaches for Diagnosing Melanoma Skin Lesions Through Supervised and Deep Learning Algorithms.

Authors:  J Premaladha; K S Ravichandran
Journal:  J Med Syst       Date:  2016-02-12       Impact factor: 4.460

Review 8.  Melanoma Early Detection: Big Data, Bigger Picture.

Authors:  Tracy Petrie; Ravikant Samatham; Alexander M Witkowski; Andre Esteva; Sancy A Leachman
Journal:  J Invest Dermatol       Date:  2018-10-25       Impact factor: 8.551

9.  Skin cancer recognition by using a neuro-fuzzy system.

Authors:  Bareqa Salah; Mohammad Alshraideh; Rasha Beidas; Ferial Hayajneh
Journal:  Cancer Inform       Date:  2011-02-02
  9 in total

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