Medil AIMedia resources
Current, attributable facts for journalists, researchers, patient organizations, professional publications, and independent reviewers. Product descriptions below are grounded in the September 2026 Medil AI preprint and identify the dated implementation snapshot they describe.
Ariel Israel and Eugene Merzon
Preprint version 1, posted 7 September 2026. DOI 10.20944/preprints202609.0448.v1 · Canonical preprint page · Evidence map and citation downloads
Medil AI is a multilingual Android and iOS app that connects source-linked medicine information with prescription capture, reminders, patient-confirmed dose records, dose-sequence support, and a medical diary. Health measurements can be imported from Health Connect or HealthKit, or entered after camera-assisted reading of a separate device's display and user confirmation.
The September 2026 preprint describes Medil AI version 4.17 as a multilingual Android and iOS platform designed around the period between a prescription and the next consultation. It connects medicine information from public regulatory or authoritative sources with prescription capture, personal instructions, reminders, patient-confirmed dose records, and a diary. The implementation snapshot reports source-linked medicine information for 12 country environments and translation into 20 languages. It also documents prescribed dose-sequence support, imports from Health Connect and HealthKit, and camera-assisted transcription of values displayed by separate home-monitoring devices. Proposed prescription fields and camera-read values remain editable and require user review before saving. The diary can place medication-use records, notes, care events, and selected health readings on a dated timeline for display, export, or print. Reporting followed mERA and iCHECK-DH and organized the implemented functions as one connected path from medicine information through daily records to preparation for the next consultation.
Please attribute these descriptions to Medil AI or the cited preprint rather than presenting them as an independent review finding.
| Product | Medil AI |
|---|---|
| Publisher | Medil Health Technologies Ltd |
| Platforms | Android and iOS |
| Research snapshot | Version 4.17, documented from released screens and public guides on 2026-09-03 |
| Reporting approach | Descriptive design and implementation study; reporting informed by mERA and iCHECK-DH |
| Medicine sources | The preprint reports public regulatory or authoritative sources for 12 country-specific data environments and a Europe-wide authorization layer for other European countries. |
| Language access | The preprint reports translation of supported medicine content into 20 languages, right-to-left layouts, cross-script search, transliteration, and text-to-speech. |
| Connected workflow | Source-linked medicine information, editable prescription-image proposals, personal instructions, reminders, self-reported full or partial dose records, prescribed dose sequences, and a combined diary. |
| Measurement records | Manual entry, authorized Health Connect or HealthKit imports, and camera-assisted transcription from a separate home-monitoring device display, with user review before saving. |
| Official distribution | Google Play · App Store |
The paper's central design is continuity: the same confirmed treatment plan connects what was prescribed, what the user can look up, reminders, what the user records, and what can be reviewed at the next visit.
Table 3 documents 12 country-specific medicine-data environments; Figure 4 shows source-linked information, translation, right-to-left presentation, Cyrillic search, and transliteration.
Figure 6 documents camera-assisted transcription of visible values into editable fields, user review before saving, and a diary that places selected readings beside medication-use records.
Figure 5 documents a dose-sequence confirmation screen that lists phases, doses, and durations before scheduling and asks the user to compare it with prescriber instructions.
| Paper reference | Documented subject |
|---|---|
| Table 3 (pages 7-8) | Medicine-data environments |
| Table 4 (pages 9-11) | Implemented functions and access status |
| Figure 2 (page 12) | Prescription-image workflow |
| Figure 3 (page 13) | Reminder, dose record, and external-AI handoff |
| Figure 4 (page 14) | Language and cross-script access |
| Figure 5 (page 15) | Prescribed dose-sequence confirmation |
| Figure 6 (pages 16-17) | Camera-assisted reading and the combined diary |
For detailed descriptions of every table and figure, use the research evidence map.
Ariel Israel and Eugene Merzon authored the preprint. The paper states that Ariel Israel created Medil AI, is founder CEO of Medil Health Technologies Ltd, and may benefit financially from adoption. Eugene Merzon declared no competing interest. The authors reported no financial support for the research, authorship, or publication.
The report used software, public product documentation, demonstration records, and screens without identifiable patient information. It involved no research participants or participant dataset.
Screens contain synthetic demonstration records. Confirm the intended context and current caption before publication.
Independent reviewers retain full editorial control. Medil provides factual source material, testing access, and assets. Medil employees and contractors identify their affiliation when participating in public discussions.
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