Identify hospital patients count
using AI
Below is a free classifier to identify hospital patients count. Just upload your image, and our AI will predict the number of patients in various hospital wards. - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("hospital-patients-count", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/hospital-patients-count/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/hospital-patients-count/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the number of patients in various hospital wards..
This pretrained image model uses a Nyckel-created dataset and has 13 labels, including 1-5, 1001+, 101-200, 11-20, 201-300, 21-30, 301-400, 31-40, 401-500 and 41-50.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the number of patients in various hospital wards.).
Whether you're just curious or building hospital patients count detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify hospital patients count at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Patient Flow Management: The false image classification function can monitor real-time hospital patient counts to improve operational efficiency. By accurately identifying the number of patients present, hospitals can optimize resource allocation, staff scheduling, and bed management.
- Emergency Response Planning: This function aids in planning and responding to emergencies by providing up-to-date patient counts. Hospitals can utilize this data to enhance their response strategies during peak periods, ensuring they are adequately prepared for surges in patient volume.
- Capacity Forecasting: Hospitals can employ the false image classification function to forecast patient capacity based on current and historical data. This insight helps in anticipating future demands, allowing for better long-term resource planning and financial budgeting.
- Compliance and Safety Monitoring: The function can be used to maintain compliance with health regulations by monitoring patient counts in waiting areas and treatment rooms. By ensuring that patient numbers do not exceed safety limits, hospitals can enhance patient safety and reduce the risk of overcrowding.
- Operational Reporting: By integrating patient count data into business intelligence systems, hospitals can generate detailed operational reports. These reports provide insights into patient flow trends, helping management identify bottlenecks and improve overall efficiency.
- Telehealth Services Optimization: With accurate patient count data, hospitals can better manage telehealth resources. They can ensure that enough staff is available to handle virtual visits, improving patient satisfaction and overall service delivery.
- Patient Demographics Analysis: The classification function can help in analyzing patient demographics by location and time. This information enables hospitals to tailor their services and marketing strategies to specific populations, ultimately enhancing community health programs and outreach efforts.