WO2026047605 - WELLNESS MANAGEMENT APPLICATION WITH AI-POWERED INFECTION DETECTION
National phase entry is expected:
Publication Number
WO/2026/047605
Publication Date
05.03.2026
International Application No.
PCT/IB2025/058710
International Filing Date
29.08.2025
Title **
[English]
WELLNESS MANAGEMENT APPLICATION WITH AI-POWERED INFECTION DETECTION
[French]
APPLICATION DE GESTION DU BIEN-ÊTRE AVEC DÉTECTION D'INFECTION ASSISTÉE PAR IA
Applicants **
LIGHT AI INC.
Inventors
WHITEHEAD, Peter Douglas
GUPTA, Udit
KRAYACICH, Lucas
Priority Data
63/688,634
29.08.2024
US
63/727,468
03.12.2024
US
Application details
| Total Number of Claims/PCT | * |
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| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
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| Pages of Specification | * |
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International Searching Authority |
CIPO
* |
| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| * | |
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| 译文 |
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* The data is based on automatic recognition. Please verify and amend if necessary.
** IP-Coster compiles data from publicly available sources. If this data includes your personal information, you can contact us to request its removal.
Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2300 | |
| EPO | Filing, Examination, Granting | 14132 | |
| Japan | Filing, Examination, Granting | 2309 | |
| South Korea | Filing, Examination, Granting | 2502 | |
| USA | Filing, Examination, Granting | 6540 |
Total:
27,783
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Abstract[English]
A wellness management application enables automated diagnosis of a throat infection based on a throat image. A captured image is segmented into a plurality of image segments corresponding to different anatomical structures. A set of machine learning models are applied to the respective image segments to generate respective prediction scores indicative of likelihood of infection. Each of the set of machine learning models are independently trained based on labeled images of the corresponding anatomical structure. The results of the respective models may be aggregated to generate an aggregate prediction. Furthermore, various visual representations may be generated that illustrate respective contributions of different regions of the image to the prediction. The wellness management application may be integrated with a telehealth system to facilitate diagnosis and treatment of infections.[French]
Une application de gestion du bien-être permet un diagnostic automatisé d'une infection de la gorge sur la base d'une image de la gorge. Une image capturée est segmentée en une pluralité de segments d'image correspondant à différentes structures anatomiques. Un ensemble de modèles d'apprentissage automatique est appliqué aux segments d'image respectifs pour générer des scores de prédiction respectifs indiquant la probabilité d'une infection. Chacun de l'ensemble de modèles d'apprentissage automatique est entraîné indépendamment sur la base d'images étiquetées de la structure anatomique correspondante. Les résultats des modèles respectifs peuvent être agrégés pour générer une prédiction agrégée. En outre, diverses représentations visuelles peuvent être générées qui illustrent les contributions respectives de différentes régions de l'image à la prédiction. L'application de gestion du bien-être peut être intégrée à un système de télésanté pour faciliter le diagnostic et le traitement des infections.