DEEP LEARNING LYME DISEASE DIAGNOSIS

Techniques for diagnosing Lyme disease are presented. The techniques may include obtaining a digital photo of a skin lesion, providing the digital photo to a deep learning convolutional neural network, such that an output diagnosis is provided. The deep learning convolutional neural network may be t...

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Bibliographic Details
Main Authors NG, Elise, BURLINA, Philippe M, JOSHI, Neil J, BILLINGS, Seth D, AUCOTT, John N
Format Patent
LanguageEnglish
Published 11.11.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DIAGNOSIS
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Summary:Techniques for diagnosing Lyme disease are presented. The techniques may include obtaining a digital photo of a skin lesion, providing the digital photo to a deep learning convolutional neural network, such that an output diagnosis is provided. The deep learning convolutional neural network may be trained using a training corpus including a plurality of digital training images annotated according to one of a plurality of training image diagnoses, where the plurality of training image diagnoses include at least one Lyme disease type, normal skin, and at least one non-Lyme skin lesion type, and where the plurality of digital training images include multiple digital photographs publicly available on the internet. The techniques can include outputting the output diagnosis.
Bibliography:Application Number: US201917278377