WO2026132964 - PREDICTING HEALTH STATES OF CATS
National phase entry is expected:
Publication Number
WO/2026/132964
Publication Date
25.06.2026
International Application No.
PCT/IB2025/062327
International Filing Date
02.12.2025
Title **
[English]
PREDICTING HEALTH STATES OF CATS
[French]
PRÉDICTION D'ÉTATS DE SANTÉ DE CHATS
Applicants **
SOCIETE DES PRODUITS NESTLE SA
Inventors
MCGOWAN, Ragen Trudelle-Schwarz
LANGENFELD-MCCOY, Natalie
DUSSAN, Helber
ARNDT, Olivia
SCHOENECK, Nicholas
KAKARLAPUDI, Nikhil
RAJEEV, Devanand
PANDA, Sanjana
JAIN, Siddharth
GANESHKUMAR, Praveenkumar
RASTOGI, Somil
Priority Data
63/736,050
19.12.2024
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 |
EPO
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| 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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| Translation |
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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 | 2200 | |
| EPO | Filing, Examination, Granting | 9355 | |
| Japan | Filing, Examination, Granting | 2214 | |
| South Korea | Filing, Examination, Granting | 2200 | |
| USA | Filing, Examination, Granting | 4740 |
Total:
20,709
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Abstract[English]
The present disclosure provides systems and methods for predicting the health state of cats, e.g., renal health. The method can include obtaining load data over time from interactions of a cat with a litter box, e.g., a smart litter box system, and using the load data in conjunction with a machine learning model with feature recognition of at least one feature based on the load data that indicates compromised health. The method can also include predicting the compromised renal health of the cat is with at least about 75% renal precision using at least a 0.5 probability threshold based on the feature recognition of the at least one feature.[French]
La présente divulgation concerne des systèmes et des procédés de prédiction de l'état de santé de chats, par exemple, leur santé rénale. Le procédé peut comprendre l'obtention de données de charge au cours du temps à partir d'interactions d'un chat avec un bac à litière, par exemple, un système de bac à litière intelligent, et l'utilisation des données de charge conjointement avec un modèle d'apprentissage automatique avec reconnaissance d'au moins une caractéristique, sur la base des données de charge, qui indique une santé compromise. Le procédé peut également comprendre la prédiction de la santé rénale compromise du chat avec une précision rénale d'au moins environ 75 % à l'aide d'au moins un seuil de probabilité de 0,5 sur la base de la reconnaissance de ladite au moins une caractéristique.