EHR Prediction

Clinical encoder models predicting readmission, mortality and similar outcomes.

1in Indonesia

Named Models

NYUTronNYU LangoneReleasedJun 2023Runs onnot in the notesClassLLMNYU Langone clinical language model for EHR prediction. Readmission AUC 79.87% (temporal test) and 78.70% (prospective); in-hospital mortality AUC 94.9%. Deployed through the EHR over HL7 FHIR from January to April 2022.Commercial use: not stated; Jakarta hosting: unknown; Indonesian support: not stated

ACE-AISynapxeReleasednot in the notesRuns onnot in the notesClasstabularCardiovascular risk model listed by Synapxe (Singapore).Commercial use: not stated; Jakarta hosting: unknown; Indonesian support: not stated

CAPESynapxeReleasednot in the notesRuns onnot in the notesClasstabularPneumonia severity model listed by Synapxe (Singapore).Commercial use: not stated; Jakarta hosting: unknown; Indonesian support: not stated

Where this comes from

Models the research names for this use case. Research, with sources on each model record.

Who Runs It

production, 4research, 1planned, 1

Synapxe (Singapore public healthcare)Country: SingaporeACE-AIVendor: SynapxeproductionDate–Listed by Synapxe; no dates givenEvidence: government statementConfidence: mediumSource: synapxe.sg

Synapxe (Singapore public healthcare)Country: SingaporeCAPEVendor: SynapxeproductionDate–Listed by Synapxe; no dates givenEvidence: government statementConfidence: mediumSource: synapxe.sg

Synapxe (Singapore public healthcare)Country: SingaporeCKD and readmission modelsVendor: SynapxeproductionDate–Listed by Synapxe; no dates givenEvidence: government statementConfidence: mediumSource: synapxe.sg

Synapxe (Singapore public healthcare)Country: SingaporeHEALIX (analytics platform)Vendor: SynapxeproductionDate–Listed by Synapxe; no dates givenEvidence: government statementConfidence: mediumSource: synapxe.sg

NYU LangoneCountry: USANYUTronVendor: NYU LangoneresearchDateJan 2022Prospective trial over 29,286 discharges via EHR (HL7 FHIR), Jan to Apr 2022; prospective readmission AUC 78.70%Evidence: academic paperConfidence: highSource: nature.com

Kementerian Kesehatan (Kemenkes)Country: IndonesiaAI diabetes risk prediction to narrow mass screening (model not stated)Vendor: not statedplannedDate23 Jul 2025Model would flag about 30 percent of roughly 90 million people as higher risk so screening budgets go furtherEvidence: government statementConfidence: mediumSource: cnbcindonesia.com

Where this comes from

Documented uses by named organisations. The evidence column says who made the claim.

Candidate Models

SEA-HELM leaderboard, 58 models, SEA average

A general benchmark for this model class, not a test on this use case. SEA average and per-language (incl. Indonesian) scores for open-weight models. Higher is better. Showing 10 of 11.

Qwen3.6-35B-A3BAlibaba (Qwen) maintainer-run73.86

Qwen3.5-35B-A3BAlibaba (Qwen) maintainer-run73.55

gemma-3-27b-itGoogle maintainer-run64.54

Gemma-SEA-LION-v4-27B-ITAI Singapore maintainer-run64.35

gpt-oss-20bOpenAI maintainer-run60.64

Llama-3.3-70B-InstructMeta maintainer-run60.44

Qwen3-8BAlibaba (Qwen) maintainer-run60.33

GLM 4.7 FlashZ.ai (Zhipu) maintainer-run53.76

Gemma-3-4B-itGoogle maintainer-run47.84

Nemotron 3 Nano 30B-A3BNVIDIA maintainer-run46.89

050100

Nemotron-SEA-LION-v4.8-120B-A12BAI Singapore, LLMReleasedSep 2026open weightsIndonesian statedhas scoreslast 18 months

Nemotron-SEA-LION-v4.8-30B-A3BAI Singapore, LLMReleasedSep 2026open weightsIndonesian statedhas scoreslast 18 months

Qwen-SEA-LION-v4.5-27B-ITAI Singapore, LLMReleasedMay 2026open weightsIndonesian statedhas scoreslast 18 months

Qwen3.6-35B-A3BAlibaba (Qwen), LLMReleasedApr 2026open weightsruns on edgehas scoreslast 18 months

Nemotron 3 SuperNVIDIA, LLMReleased2026open weightsIndonesian statedhas scoreslast 18 months

Nemotron 3.5 Lightning 30B-A3BNVIDIA, LLMReleased2026open weightsIndonesian statedhas scoreslast 18 months

gpt-oss-120bOpenAI, LLMReleasedAug 2025open weightsIndonesian statedhas scoreslast 18 months

Granite 4.2 8BIBM, LLMReleasedSep 2026open weightshas scoreslast 18 months

Hy4-previewTencent, LLMReleasedAug 2026open weightshas scoreslast 18 months

GLM-5.3Z.ai (Zhipu), LLMReleasedAug 2026open weightshas scoreslast 18 months

Showing 10 of 401. All models of this class

Where this comes from

Derived, not researched: models in the directory whose class matches a class this use case uses, excluding family records and models shut down or deprecated. Ranked by how many fit facts they meet, then by release date. Each fit fact is read from the model record.

Use Case

Industry: healthcare and pharma
Model classes: LLM
Benchmarks or datasets: not in the notes
Regulatory notes: Surat Edaran Menkominfo 9/2023 Etika Kecerdasan Artifisial, Kementerian Komunikasi dan Informatika (now Kementerian Komunikasi dan Digital)EHR prediction is an AI-based service run by an electronic system operator, and the circular asks such operators to build and use AI on the values of inclusivity, transparency, humanity and security.
UU 27/2022 Pelindungan Data Pribadi, DPR and President of the Republic of Indonesia (administered by Kementerian Komunikasi dan Digital)EHR prediction processes health data of patients, which the law treats as a specific category of personal data, so the controller needs a lawful basis, must protect the data and must honour data subject rights.
UU 17/2023 Kesehatan, DPR and President of the Republic of Indonesia (administered by Kementerian Kesehatan)EHR prediction is used in delivering health services or handling patient records, which this law governs through rules on medical records, health information systems, health technology and medical devices.
EU AI Act, Regulation (EU) 2024/1689 (international), European UnionEHR prediction is software that may qualify as a medical device or a safety component of one; the EU AI Act treats such AI as high-risk when the product is placed on the EU market.

Where this comes from

From the industry tracks T08 to T10 of the research notes.

R&D Topics

Links to R&D topics are awaiting review.

Where this comes from

Which R&D topics would most change this use case. Drafted by Claude from the topic definitions and the use case; proposed until approved.

Incidents

Epic Systems’s Sepsis Prediction Algorithms Revealed to Have High Error Rates on Seriously Ill PatientsUnited States, 2021-08-01, safetyEpic System's sepsis prediction algorithms was shown by investigators at the University of Michigan Hospital to have high rates of false positives and false negatives, allegedly delivering inaccurate and irrelevant information on patients, contrasting sharply with their published claims.
Optum Algorithmic Health Risk Scores Reportedly Underestimated Black Patients' NeedsUnited States, 2019-10-24, discriminationResearchers analyzing an Optum algorithm used by a large academic hospital reportedly found evidence that it tended to under-predict the health care needs of Black patients, which in turn appeared to result in lower prioritization for extra care programs compared with white patients exhibiting similar health profiles.
Purportedly AI-Generated Sepsis Alert Reportedly Prompted Potentially Inappropriate IV Fluid Administration for a Dialysis Patient, Averted by Clinician Intervention2026-02-17, safetyA nurse at St.

Where this comes from

Documented failures, harms or misuse in this kind of use, Indonesia first, then the region, then well-known cases elsewhere (AI Incident Database, OECD AI incidents monitor, reputable news). Not a claim about any deployment listed here.

In Neighbouring Countries

Synapxe with public hospitals (Hospital to Home programme)Singapore, state-owned, productionMultiple Readmissions Predictive Model (clinical theory plus machine learning)

Where this comes from

Documented deployments of this use case in Malaysia, Singapore, Thailand, Vietnam and the Philippines, each with its source.

Opportunities

Opportunities are awaiting review.

Where this comes from

Gaps found by rule in what the directory holds for this use case. Each is a proposal for review.

Links

IndustryHealthcare40 use cases, 66 deployments

Use CaseEHR PredictionHealthcare

Models

NYUTronNYU Langone, LLM

ACE-AISynapxe, tabular

CAPESynapxe, tabular

Who Runs It

Kementerian Kesehatan (Kemenkes)Planned, 23 Jul 2025

NYU LangoneResearch, Jan 2022

Synapxe (Singapore public healthcare)In production

Synapxe (Singapore public healthcare)In production+2 more

Graph

Models 3

NYUTronNYU Langone, LLM

ACE-AISynapxe, tabular

CAPESynapxe, tabular

Deployments 6

NYU LangoneNYUTron, USA Synapxe (Singapore public healthcare)ACE-AI, Singapore Synapxe (Singapore public healthcare)CAPE, Singapore Kementerian Kesehatan (Kemenkes)AI diabetes risk prediction to narrow mass screening (model not stated), Indonesia Synapxe (Singapore public healthcare)CKD and readmission models, Singapore Synapxe (Singapore public healthcare)HEALIX (analytics platform), Singapore

Sources

Client Challenge nature.com https://www.nature.com/articles/s41586-023-06160-y
Health AI projects | Synapxe synapxe.sg https://www.synapxe.sg/healthtech/health-ai

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "EHR Prediction", https://aurion.semai.id/usecases/hc-ehr-prediction/, records of October 2026.