AIMC Topic: Dogs

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To see or not to see the vet: A vignette-based study of decision-making by UK dog owners regarding seeking veterinary care for commonly presenting conditions.

PloS one
Barriers to accessing veterinary-care for dog-owners are diverse and dynamic, and widely accepted as major canine welfare threats because of potential non-, under- or delayed treatment. Owner knowledge and perceptions are recognised as key influences...

Exploring DNA methylation profiles in blood samples of canine gastrointestinal lymphoma.

PloS one
Blood-based testing represents a valuable tool for the detection and monitoring of patient conditions in both human and veterinary medicine. When conventional tissue-based diagnosis is challenging, blood-derived measurements allow for minimally invas...

When used for veterinary triage, artificial intelligence models recognise emergencies but are more likely than veterinary staff to flag non-urgent cases as urgent.

The Veterinary record
BACKGROUND: This study assesses the capability of ChatGPT and nurses in accurately triaging emergency patients compared to veterinarians. METHODS: Retrospective observational study of canine patients that presented at a private veterinary specialist ...

A Machine Learning-Empowered Quantitative Structure-Activity Relationship Model for Predicting the Plasma Half-life of Drugs in Dogs.

The AAPS journal
Understanding a drug's plasma half-life is essential in guiding dosage regimens and optimizing therapeutic outcomes, particularly in the early stages of drug development. By using published pharmacokinetic data from Food Animal Residue Avoidance Data...

Reconstructing strontium-90 intake in beagles using neural networks: a data-driven assessment of historical inhalation records.

Journal of radiological protection : official journal of the Society for Radiological Protection
Dose estimation in response to internal radionuclide exposures requires reconstruction of the initial intake activity, which is frequently unknown due to the absence ofdata. In such scenarios, intake is inferred from bioassay measurements obtained at...

Evaluating machine learning approaches for host prediction using H3 influenza genomic data.

PloS one
BACKGROUND: H3 influenza A viruses (IAV) have been shown to frequently cross the species barrier which can be an important factor in sustained transmission and spread. Machine learning methods have been widely explored for host prediction of IAV usin...

A gastric retentive robotic capsule enables emergency-prepared and responsive oral drug delivery in canine models.

Science advances
Existing oral drug delivery modalities often fall short in medical emergencies due to the absence of readily deployable, internalized drug storage and delivery mechanisms that combine long-term standby with rapid activation. To address this challenge...

Automated segmentation of canine pulmonary masses in CT imaging using AI.

The veterinary quarterly
Primary pulmonary lung cancer is rare in dogs, and clinicians increasingly rely on advanced imaging for diagnosis and treatment planning. However, manual lesion segmentation can be time-consuming and subject to operator variability. This retrospectiv...

Precise path planning for robot-assisted craniotomy: a CT-driven virtual center method.

Biomedical physics & engineering express
. Craniotomy is a critical prerequisite for numerous neuro-surgeries, including intracranial tumor resection and cerebral hemorrhage decompression. However, conventional manual craniotomy methods are often time-consuming, labor-intensive, and associa...

Interpretating SPR-Derived Reaction Kinetics via Self-Organizing Maps for Diagnostic Applications.

ACS sensors
Biosensors emerge as promising, cost-effective infectious disease diagnostics in resource-limited settings, requiring neither laboratory infrastructure nor specialized personnel. Surface plasmon resonance (SPR)-based biosensors remain preeminent for ...