Geriatric
Nimblemind helps healthcare AI teams prepare multimodal geriatric datasets in hours with automation, governance, and pipelines that reduce manual work.
Nimblemind was used in a recent pain prediction study involving geriatric patients
With data sourced from wearables, patient surveys, and EMR data, the model accurately predicted evening pain spikes three days in advance.
Passive data collection alongside clinical care
Zero disruption to existing data pipelines
94% accuracy in real-world use
Geriatric Specialty
Upload electronic health records, assessments, wearables, and more without manual formatting steps. Nimblemind structures, labels, and prepares datasets automatically, then exports directly into your data pipeline.
Reduce prep time
Go from raw files to labeled corpuses in hours using built-in automation
Keep governance tight
Assign and revoke access by role or study with built-in audit logs
Nimblemind is built to ingest and process the formats most relevant to geriatric studies and care models.
Modality
Examples
EMR and Clinical Notes
Diagnoses, vitals, discharge summaries, medications
Cognitive Assessments
MMSE, MoCA, Clock Drawing Test
Functional Assessments
ADLs, IADLs, Timed Up and Go, Barthel Index
Imaging Data
Brain MRI, DEXA scans, chest X-rays
Wearables and Sensor Data
Step count, sleep tracking, heart rate variability
Lab Results
Hemoglobin, eGFR, vitamin levels, inflammatory markers
Pharmacy Data
Medication lists, dosage schedules, drug interactions
Speech and Audio Data
Voice recordings
Social Factors
Living conditions, caregiver access, SDOH, income
