DB-Mips


Introduction
Objectivity
DB-Mips
 Mapping
 Accuracy
Telemedicine
Bibliography
 Scientific Links
 Curriculum

D Software
DB-Mips info


Skinlesions

Introduzione
Accuratezza
Telemedicina
Bibliografia
Contatti
Links
Curriculum


Sponsor
 DB-Mips
DDAX Software

Accuracy

The main goal of the aided diagnosis is to develop machines that will help clinicians in their daily practice. For this reason, the instrument must be easy to use, fast and not based on subjective evaluation. When a System-aided interpretation is based on clinician's assessments the results are obviously based on a poor engine. Moreover the hidden trap is the fact that a clinician himself can not be the "gold standard" for the diagnosis. A real false negative has not been seen by the dermatologist. For this reason many scientific studies are not very useful when reporting high accuracy with machines that depend on previous expert examination because he is a filter for the reality of facts. Plus we also know that Systems with poor quality only "see" trivial melanoma. For this reason, it is apparently easy to reach very high sensibility on such machines, but the results are false. Some studies report a sensitivity of 100%, forgetting that the histology itself, which is the "gold standard", does not reach such value. If a study is based on aprevious clinician's examination, we must consider his error and multiply the sensibility for a correction factor. Otherwise it would be necessary to employ skin cancer registries and multicentered validations, as was done during the development of the DB-Mips System.

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DB-Mips actually employs ANN and Similarity classifiers. The results obtained during the last decade by independent clinicians who used the DB-Mips are reported on this page. Please note how the release version and the accuracy values have increased over the years. Subjective , non-reproducible algorithms have been replaced by objective and reliable variables. The experts use their common sense and machines do the rest.


Aided diagnosis of melanoma: DB-Dermo, DB-Mips accuracy by publications

 Pubblication

Classifier

DB-Mips Release

 Accuracy
 D.Piccolo et .
"Dermoscopic Diagnosis..."
Br. J. Dermatology. 2002

 Neural Network
100 samples

DDA-Mips n.n. 1995
Sens :92
Spec :74
Seidenari S. et al
"Digital videomicroscopy ..."
Melanoma Res. 1999 Apr;9(2):163-71.

Discrim. Anal.

  DDA-Mips n.n. 1995
Sens :100
Spec :92
Burroni M.et al.
"Early diagnosis of melanoma"
Melanoma. Res. 1997 ; 7(Suppl):S58.

 Neural Network
200 samples

   DDA-Mips 2.0 1996
Sens :98
Spec :82
Burroni M.
"Understanding Digital Melanoma"
Melanoma Res. 2001;Vol. 11, Supp.1:22-23

 Similarity
1400 samples

  DDM-Mips 1.0 2000
Sens :98
Spec :84
Rubegni P. et al
"Digital dermoscopy analysis ".
J Invest Dermatol. 2002 Aug;119(2):471-4.

Artificial Neural Network

 DDM-Mips 1.0 2000
Sens :94
Spec :94
Rubegni P. et al.
"Automated diagnosis of pigmented skin lesions"
Int J Cancer. 2002 Aug 20

Artificial Neural Network

 DDM-Mips 8.2 2001
Sens :96
Spec :96

 
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Copyright Burroni 1999-2001
A copy of this documentation and pictures are deposited.
Any permission of copies must be explicitly asked.

 
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