Zero-burden Risk Assessment for Test-free Screening &

Predictive Prognosis of Alzheimer's Disease & Mild Cognitive Impairment

Ishanu Chattopadhyay, PhD

Assistant Professor of Internal Medicine

Institute of Biomedical Informatics

& Computer Science

University of Kentucky

Zero Knowledge Discovery

Zero-Burden Co-morbid Risk Score

"Test-free" screening
No new tests or Bloodwork
Use data already in patient file
No specific data demands
GENERALIZABLE TO OTHER TARGETS (Autism, Alzheimer's Disease)

Reduce screen failue rate

ASD

ADRD

IPF

ZCoR

Diagnostic procedural codes & prescriptions

ICD

Explainable glassbox Visualizations

Universal Point-of-care Screening

Enable early diagnosis

Target PF/IPF or ILDs broadly

Seamless background integration with EHR/clinical workflows

Technology Overview

2. Conventional AI attempts to model the physician

Current State of Art

1. Use of AI in point-of-care diagnostic workflow is limited

ZCoR

Use under-utilized diagnostic modalities
Discover co-morbidity patterns
Go beyond know risk factors
Personalized risk patterns

*Chattopadhyay, Ishanu, and Hod Lipson. "Abductive learning of quantized stochastic processes with probabilistic finite automata." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1984 (2013): 20110543.

Curated Disease-agnostic Features | Odds ratio dictionaries combined with multi-stage LGBMs | Specialized HMM based Longitudinal Tracking*

Most predictive AI platforms, including those from Merative, PathAI, Tempus, Google Health, and Microsoft, primarily rely on imaging data for early detection.

State of the art screening approaches are inadequate

Standard AI

	ZCoR	Competition
Autism	>83%	"obvious"
Alzheimer's Disease	~90%	60-70%
Idiopathic Pulmonary Fibrosis	~90%	NA
MACE	~80%	~70%
Bipolar Disorder	~85%	NA
CKD	~85%	NA
Rare Cancers (Bladder, Uterus)	~75-80%	Low
Suicidality (with CAT-SS)	98% PPV	Low

Validation

CELL Reports

Performance comparison with Li et al.*

*Li, Qian, Xi Yang, Jie Xu, Yi Guo, Xing He, Hui Hu, Tianchen Lyu et al. "Early prediction of Alzheimer's disease and related dementias using real‐world electronic health records." Alzheimer's & Dementia 19, no. 8 (2023): 3506-3518

dddd

Use only data available at point-of-care (diagnostic codes, procedures and prescriptions)
AUC (~94-97%) oos
Likelihood ratio >80
Validated in over 12M patients in Marketscan, UChicago, AllofUS cohorts

ZCoR Screening

Performance

Screening performance over time