Related Objects of Interest: chair , person , monitor , doctor , stand , pillow , bed , nurse , anesthesia machine bottom , anesthesia machine top

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Top Patient Datasets and Models

The datasets below can be used to train fine-tuned models for patient detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.

At the bottom of this page, we have guides on how to train a model using the patient datasets below.

Object Detection snap yolonas yolonas-s

Crimson Phoenix

9974 images

Chest Seal - HALO Combat-Action-Tourniquet Cric-Key Emergency Trauma Bandage Fox Eye Shield King Laryngeal Tube (King-LT)NasoPharyngeal Airway (NPA)Needle Chest Decompression Non-ReBreather (NRB)Non-ReBreather -NRB-Oropharyngeal Airway (OPA)Patient Wristband SAM Junctional Tourniquet

Object Detection Model snap

activity_module

7702 images1 model

standing bending patient on stretcher patient on wheel chair sitting sleeping using_phone walking

Instance Segmentation Model yolov8 yolov8s yolov8m

1449 images4 models

wheelchair ct-scanner ct-scanner-ring patient scanner-bed stretcher tech

Object Detection

0

4971 images

bed danger fall person stand wheelchair lie move na patient sit walker

Instance Segmentation

704 images

bed chair document monitor person sign tie window doctor name plate patient room plate

Object Detection

hospital_monitor_36

140 images

caregiver cleaner patient

Object Detection

1970 images

person hospital-beds hospital-tool hospital-worker patient

Object Detection Model snap

1970 images1 model

person hospital-beds hospital-tool hospital-worker patient

Object Detection

Fuse Machine Demo

756 images

face monitor pillow blue scrubs clipboard doctor hospital bed lady doctor nurse patient saline bottle stethoscope white blanket white coat

Object Detection

721 images

face monitor pillow blue scrubs clipboard doctor hospital bed lady doctor nurse patient saline bottle stethoscope white blanket white coat

Object Detection Model snap

1046 images1 model

people area nurse patient

Object Detection

249 images

glove head logo mask person limb patient surgical cap

Object Detection Model snap

3107 images1 model

Doctor Nurse Patient Relatives

Object Detection

126 images

Date Doctor Duration Frequency Medicine Patient dose

Object Detection Model snap yolov11 yolov11n

1596 images2 models

Normal PD-patient acute-ischemic-stroke control

Object Detection

szeivan2729@gmail.com

495 images

cracked tongue geographic tongue normal tongue patient scalloped tongue

Object Detection

45 images

Head Wall System Vital Signs Monitor band-aid bandage blood pressure cuff doctor family nurse patient stethoscope thermometer

Instance Segmentation Model roboflow-3-n-seg

2843 images2 models

bed augmentin cefazolin patient prepstick tourniquet

Object Detection Model snap

398 images1 model

ambulance angry auto background bear board can down egg face food foot good healthy house human letter medical money number

Object Detection

2069 images

block bridge cone crosswalk danger bomb evil patient prop safety spy thief tumble

Object Detection Model snap

393 images1 model

Patient seizure Patient sleeping docter empty bed family heart attack patient patient awake patient coughing patient sitting patient standing staff

Object Detection

393 images

Patient seizure Patient sleeping docter empty bed family heart attack patient patient awake patient coughing patient sitting patient standing staff

Object Detection Model snap

393 images1 model

Patient seizure Patient sleeping docter empty bed family heart attack patient patient awake patient coughing patient sitting patient standing staff

Object Detection

393 images

Patient seizure Patient sleeping docter empty bed family heart attack patient patient awake patient coughing patient sitting patient standing staff

Object Detection

626 images

bed danger fall person stand wheelchair lie move na patient sit walker

Object Detection

5524 images

bed danger fall person stand wheelchair lie move na patient sit walker

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