Dietitians
Spend your time on the cases that need your judgment
- AI handles meal analysis and calculations first
- The review screen keeps accept / edit / reject in your hands
- Patient education records and follow-up results in one place
Designed for Taiwan's care teams
Help your dietitian team care for more patients,
while preserving clinical judgment.
DietMate uses AI to support food recognition, risk screening, and long-term nutrition tracking, so dietitians can focus on clinical decisions and improve both quality and efficiency of care.
Healthcare security
Designed with reference to healthcare security standards
Taiwan food data
Local food database
3x care efficiency
Boosts dietitian team capacity
Which diabetes patients have had wider glucose swings over the past two weeks?
Live Demo
A workbench built for dietitians
Client follow-up, photo recognition, and online chat in a single workflow. Use the sidebar on the left to explore on your own.
The Live Demo needs a wider screen
The workbench is designed for desktop. Open this page on a computer to click through all eight screens yourself, or book a briefing and we'll walk through your department's actual workflow.
Book a briefing01/Recognize
Care pathway
Recognize, review, track, alert, research: one complete care pathway.
Recognize
User: Patient uploads a meal photo
System: System returns structured nutrition data
Review
User: Dietitian reviews the AI suggestion
System: Accept, edit, or return it with a note
Track
User: Set tracking metrics and follow-up frequency
System: Long-term trends are charted automatically
Alert
User: System checks patients against risk criteria
System: Flagged patients go to today's to-do list
Research
User: Query all patients in natural language
System: Population statistics and outcome analyses can be exported
Each stage spells out both what the user does and what the system returns, so during rollout you can map it directly against your current workflow and find the gaps.
Map your workflow with us
Core Features
Four core modules for a complete nutrition care ecosystem
dietmate.platform.tw — Pending Review
Pending Review
3 meals awaiting your review
Wang Jou-anMediumLunch
Identified: grilled chicken breast, avocado, mixed greens
Calories450 kcal
Protein35 g
Carbs52 g
AI suggestion: Good protein intake, low fat ratio. Consider adding healthy fat sources.
Chang Che-weiHighSnack
Identified: chocolate brownie, vanilla ice cream
⚠ 203 kcal over target, intervention suggested
Li Hsiao-huaLowDinner
Identified: white rice, steamed fish, stir-fried greens
AI Food Recognition
Combines deep learning and natural language processing to identify nutrients from food photos in real time, backed by a database of local Taiwanese ingredients for precise nutrition analysis.
- Food image recognition
- Real-time nutrient calculation
- Taiwanese food database
- Continuously improving model
Clinical Nutrition Decision Support
Supports professional care workflows with personalized dietary guidance and advanced nutrition analysis, helping dietitians make precise judgments.
- Personalized nutrition recommendations
- Personalized dietary guidance
- Drug–nutrient interaction analysis
- Clinical decision support system
Nutrition Tracking & Workflow Management
Long-term monitoring and trend analysis of nutritional status, with automated scheduling and multidisciplinary collaboration to streamline dietitians' daily work.
- Nutrition status charts
- Automated scheduling and reminders
- Real-time abnormal-value alerts
- Efficiency monitoring dashboard
dietmate.platform.tw — Workspace
Good morning, Dietitian Lin Ya-ting
3 meals need your review today
0
Active patients
0
Pending
0%
Met this month
0
Flags
Calorie intake this week
TargetActual
Mon
Tue
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Thu
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Recent activity
View all- Pending
Wang Po-chun uploaded a new meal
10 min ago
- Updated
Li Hsiao-hua updated health data
1 hr ago
- Watch
Chen Chien-chih has an abnormal blood glucose reading
3 hr ago
dietmate.platform.tw — Research Assistant
Which nephrology patients are consistently exceeding their potassium intake?
DietMate Research Assistant
cohort.scan(group="nephrology", metric="potassium_intake")
In the past 30 days, 11 patients exceeded the recommended potassium intake. 4 of them have missed follow-up visits for three weeks in a row.
- Chen Mei-ling30% above target3.9 g/day
- Wu Chih-hao13% above target3.4 g/day
- Hsu Chia-yuNear upper limit3.2 g/day
Create tracking listExport CSV
Query scope is bound by institutional permissions and de-identification rules. Results are still interpreted by the care team.
AI Research Assistant
Query all your patients in a single sentence. The research assistant turns the question into explicit data operations and returns patient lists, statistics, and exportable results, which the care team still interprets before anything enters care decisions.
- Natural-language queries, no SQL needed
- Bound by institutional permissions and de-identification rules
- Turn query results into tracking lists
- Export statistics as CSV
Platform Vision
Let AI take on the repetitive work,
and leave professional judgment to dietitians.
AI handles the repetition, people make the calls
Recognition, calculation, and initial screening go to AI. Every decision to accept, edit, or reject stays with the dietitian, with a traceable record.
Built around Taiwan's clinical reality
We start from local foods, hospital meal types, and your nutrition department's existing workflows. Implementation maps to how you work today instead of asking your team to change.
From one department to multiple hospitals
One data model supports everything from a single-department pilot to multi-hospital deployment, with permissions, auditing, and data scope expanding as adoption grows.
For every stakeholder
One system, answering the different questions of three roles.
Nutrition department managers
See team capacity and backlog pressure
- Pending reviews and overdue follow-ups at a glance
- Rebalance caseloads by role
- Compare implementation results across time periods
Hospital decision-makers
Expand care within your existing security framework
- Access control, auditing, and record retention designed following healthcare security guidelines
- HIS/EMR integration can be evaluated in phases
- Start with a single-department pilot, then expand
Security & integration
Security and integration come first. Then we talk implementation.
Our pre-implementation technical review covers the permission model, data flows, audit requirements, and how we connect to your existing systems. Applicable regulations and contract terms are confirmed jointly with your hospital's security, IT, and legal teams.
Role-based access
Visibility is scoped by department and role, and every action leaves an audit trail.
Data protection
Data is encrypted in transit and at rest, and exports follow your institution's de-identification rules.
Human review
AI suggestions require dietitian confirmation; responsibility for decisions stays with the care team.
FHIR R4 integrationHIS/EMR integration assessmentLab result integrationSingle sign-on (SSO)
Want to see how DietMate would work in your nutrition department?
In one online briefing, we'll walk you through the full workflow and discuss a practical implementation scope based on where your department is today.
- [email protected]
- Our team replies to implementation inquiries within 2 business days