First patients diagnosed with rare disease with assist of AI algorithm are a fact

Sqilline and a leading pharmaceutical company have partnered to apply an AI algorithm and track high-risk patients for the rare disease of Transthyretin amyloid polyneuropathy (TTR).

The aim was to support neurologists find previously undiagnosed patients by assisting them with digital technology.

For this project, Danny Platform evaluated the electronic health records of 10 leading neurological hospitals. The proprietary algorithm, with carefully pre-defined including/excluding criteria, searched for possible undiagnosed patients.

INPUT PARAMETERS:

  • Digital data collection based on electronic health records
  • 10 Leading hospitals
  • Filed – neurology
  • Specified incl/excl criteria based on symptoms are applied to identify undiagnosed patients

CHALLENGES:

  • TTR is a progressive and ultimately, a fatal rare disease that destroys nerve cells governing various bodily functions
  • Symptoms are often similar to other diseases and difficult to recognize
  • Limited awareness
  • When structured Electronic health records hold important information
  • Most symptoms are described in free text in the epicrisis

RESULTS:

  • 3 443 Total electronic epicrisis processed in seconds from all hospitals
  • 556 Total number of patient records selected by the algorithm based on the symptoms criteria
  • 30 Patient records marked as eligible

Several patients are diagnosed with TTR by genetic test after the algorithm selection

BENEFITS FOR PHYSICIANS:

  • Systematic screening of EHRs with specified criteria can identify in seconds high-risk cases for rare diseases even after patient hospitalization
  • Increased awareness and understanding of rare diseases
  • Empowering physicians with digital technology is key to patients-centricity and precision medicine
  • Improving potential collaboration between the leading hospitals (neurology, oncology) accelerates patient diagnostics

WHY DANNY PLATFORM

Danny Platform via ML algorithms selected all patients being hospitalized for neurological diseases (G60, G61, G62, G63, G64) with the specific key symptoms and symptom weight value.

The system then creates a cohort of high-risk patients for Transthyretin amyloid polyneuropathy (TTR) to be further reviewed and examined by neurologists.

Reaching the final diagnosis was a process based on a thorough clinical evaluation, detailed screening of patient profiles, application ML algorithms, and finally confirmation by a genetic test.

Sqilline’s ambition and focus are to support physicians accelerate earlier diagnosis and treatment for patients with rare diseases so they can lead better, more fulfilling lives.

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