Health Condition 1: R00-R99- Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified
Conditions
Interventions
Intervention1: Nil: Nil
Intervention2: Nil: Nil
Intervention3: Nil: Nil
Intervention4: Nil: Nil
Intervention5: Nil: Nil
Control Intervention1: Nil: Nil
Sponsors
Dr. Swetha. P
Eligibility
Inclusion criteria
Inclusion criteria: 1. Population criteria- Patients with various hematological derangements who undergo peripheral smear examination. 2. Medical history- Patients with a history of fever or clinical evidence of infection who undergo blood smear examination. 3. CBC Data: Patients with abnormal white blood cell distribution in automated analyzers. 4. Ethnicity and demographics: Consideration of diverse ethnic and demographic backgrounds to ensure the generalizability of the predictive model.
Exclusion criteria
Exclusion criteria: 1. Newborns: Excluding newborns to eliminate misdiagnosis due to the presence of nucleated red blood cells that may mimic white blood cells. 2. Lysed blood samples: Excluding patients whose samples are lysed because cells are not visualized adequately on the blood smear. 3. Inadequate clinical and lab data: Patients with inadequate clinical data are excluded, as there is no grounds to decide whether blood smear examination is warranted.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| To calculate the differential count of each type of white blood cell using AI based image analysis of the uploaded images of microscopic fields in the blood smearTimepoint: 24 hours | — |
Secondary
| Measure | Time frame |
|---|---|
| To calculate the accuracy and clinical utility of the AI model by correlating with manual differential counts.Timepoint: 1 week | — |
Countries
India
Contacts
Public ContactSwetha P
Saveetha medical college and hospital, Saveetha institute of medical and technical sciences.
Outcome results
None listed