US 12,223,643 B2
Machine-learning system for diagnosing disorders and diseases and determining drug responsiveness
Cameron Pernia, Cambridge, MA (US); Heather Tolcher, Houston, TX (US); and Evan Y. Snyder, La Jolla, CA (US)
Assigned to SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE, La Jolla, CA (US)
Appl. No. 17/616,461
Filed by Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA (US)
PCT Filed May 29, 2020, PCT No. PCT/US2020/035331
§ 371(c)(1), (2) Date Dec. 3, 2021,
PCT Pub. No. WO2020/247273, PCT Pub. Date Dec. 10, 2020.
Claims priority of provisional application 62/856,631, filed on Jun. 3, 2019.
Prior Publication US 2022/0237786 A1, Jul. 28, 2022
Int. Cl. G06T 7/00 (2017.01); G06N 20/20 (2019.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 20/69 (2022.01); G16C 20/70 (2019.01); G16H 70/40 (2018.01)
CPC G06T 7/0012 (2013.01) [G06N 20/20 (2019.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 20/693 (2022.01); G06V 20/698 (2022.01); G16C 20/70 (2019.02); G16H 70/40 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A classification system, comprising:
a user interface;
a cellular imaging device;
one or more processors; and
a non-transitory computer-readable storage device coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
receiving, from the cellular imaging device, image data comprising calcium kinetic features of neuronal cultures derived from a patient;
processing the image data through a machine-learning model to determine a diagnosis for the patient based on the calcium kinetic features, wherein the machine-learning model is trained using neuronal calcium data; and
wherein the neuronal calcium data comprises (i) basal calcium level, peak calcium transience, calcium event frequency, and calcium event amplitude, and (ii) at least one of calcium event influx and calcium event efflux; and
providing the diagnosis to the user interface, wherein the diagnosis is for bipolar disorder (BPD), Alzheimer's disease or Parkinson's disease.