AIMC Topic: Cat Diseases

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Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs.

The veterinary quarterly
A heart-convolutional neural network (heart-CNN) was developed and tested for the automatic detection of left atrial enlargement (LAE) from feline thoracic radiographs. A retrospective and multicenter study was performed. Right lateral and dorso-vent...

Comprehensive diagnostic approaches to feline toxoplasmosis: Bridging traditional methods and emerging technologies.

Virulence
is a globally distributed intracellular parasite, with felids serving as its definitive hosts and playing a central role in environmental contamination through oocyst shedding. Accurate and timely diagnosis in cats is critical for interrupting trans...

Raman spectral band imaging for the diagnostics and classification of canine and feline cutaneous tumors.

The veterinary quarterly
This study introduces Raman imaging technique for diagnosing skin cancer in veterinary oncology patients (dogs and cats). Initially, Raman spectral bands (with specificity to certain molecular structures and functional groups) were identified in form...

Accelerometer-derived classifiers for early detection of degenerative joint disease in cats.

Veterinary journal (London, England : 1997)
Decreased mobility is a clinical sign of degenerative joint disease (DJD) in cats, which is highly prevalent, with 61 % of cats aged six years or older showing radiographic evidence of DJD. Radiographs can reveal morphological changes and assess join...

Early detection of feline chronic kidney disease via 3-hydroxykynurenine and machine learning.

Scientific reports
Feline chronic kidney disease (CKD) is one of the most frequently encountered diseases in veterinary practice, and the leading cause of mortality in cats over five years of age. While diagnosing advanced CKD is straightforward, current routine tests ...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

American journal of veterinary research
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.

Artificial intelligence-based quantification of lymphocytes in feline small intestinal biopsies.

Veterinary pathology
Feline chronic enteropathy is a poorly defined condition of older cats that encompasses chronic enteritis to low-grade intestinal lymphoma. The histological evaluation of lymphocyte numbers and distribution in small intestinal biopsies is crucial for...

Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Thoracic radiographs are an essential diagnostic tool in companion animal medicine and are frequently used as a part of routine workups in patients presenting for coughing, respiratory distress, cardiovascular diseases, and for staging of neoplasia. ...

Evaluation of a Novel Veterinary Dental Radiography Artificial Intelligence Software Program.

Journal of veterinary dentistry
There is a growing trend of artificial intelligence (AI) applications in veterinary medicine, with the potential to assist veterinarians in clinical decisions. A commercially available, AI-based software program (AISP) for detecting common radiograph...

Histological classification of canine and feline lymphoma using a modular approach based on deep learning and advanced image processing.

Scientific reports
Histopathological examination of tissue samples is essential for identifying tumor malignancy and the diagnosis of different types of tumor. In the case of lymphoma classification, nuclear size of the neoplastic lymphocytes is one of the key features...