Sanjeevani
AI Mobile Health Unit (AI-MHU)
Early Detection. Lasting Impact.
Taking AI-Enabled Screening for Cancer, TB, Non-Communicable Diseases and Anaemia — with Specialist-Validated Results — to the Last Mile
Overview
| Group | Conditions | Count |
|---|---|---|
| Cancer | Breast, cervical, oral | 3 |
| Tuberculosis | Pulmonary TB | 1 |
| Non-communicable diseases | Diabetes, hypertension, COPD, diabetic retinopathy | 4 |
| Anaemia | Haemoglobin estimation | 1 |
| Total | 9 | |
Potential Impact
₹3,500 enables one individual to access comprehensive, AI-assisted screening, specialist review, and referral support.
₹1 Crore enables approximately 10,000 individuals to receive screening, specialist review, and referral support.
Background and Rationale
Non-communicable diseases now account for 63% of all deaths in India. Cancer and tuberculosis remain two of the country’s most significant public health challenges, and anaemia affects the majority of rural women and children. Effective screening and treatment exist for all of them — yet most patients are still diagnosed at advanced stages, when outcomes are worse and treatment costs far higher.
India does not lack national frameworks. The National Programme for Prevention and Control of Non-Communicable Diseases (NPCDCS), the National Tuberculosis Elimination Programme (NTEP) and Anaemia Mukt Bharat all mandate exactly this screening. The gap is not policy. It is the last mile.
Why the Last Mile Remains Unreached
Barrier 1:
Geographic and Economic
Diagnostic services are heavily concentrated in urban centres, creating travel and cost barriers that rural patients cannot cross.
Barrier 2:
Specialist Shortage
A severe lack of specialist availability at community level to interpret screenings accurately.
Barrier 3:
Fragmented Referrals
Broken pathways between initial community screening and definitive diagnostic confirmation.
The Challenge
Breast Cancer
2.38 lakh
Around one in two patients presents at an advanced stage, when treatment costs are high and outcomes poor.
Cervical Cancer
<2%
Fewer than 2% of eligible women have ever undergone cervical cancer screening.
Oral Cancer
60–80%
Among the most prevalent cancers in India, yet the vast majority of cases are diagnosed far too late.
Tuberculosis
25%
India accounts for a quarter of all global TB cases — the single largest national share. Patients seek care only after prolonged symptoms, increasing community transmission.
NCDs
~57%
One in four rural adults has hypertension, and one in seven rural people with diabetes has diabetic retinopathy — a leading cause of preventable blindness.
Anaemia
59%
54% of rural pregnant women and 68% of rural children aged 6–59 months are also anaemic.
Sources: MoHFW / NP-NCD; ICMR-INDIAB; NFHS-5; WHO Global TB Report 2025 (India’s share of global cases in 2024); published Indian epidemiological studies.
The Sanjeevani Intervention:
Delivering the Hospital to the Community
Sanjeevani brings screening to communities rather than expecting communities to travel to it. Each barrier has a direct answer:
Geographic and economic
The Sanjeevani Response
A 40-foot mobile diagnostic facility that travels to the community, removing travel cost and lost wages from the decision to be screened.Specialist shortage
The Sanjeevani Response
AI-assisted interpretation and a telemedicine and teleradiology network, placing specialist judgement within reach of any location.Fragmented referrals
The Sanjeevani Response
Structured patient navigation and referral tracking, described under Referral and Follow-Up.On board the unit
| Category | Equipment |
|---|---|
| Imaging | Digital mammographydigital chest X-raycamera for diabetic retinopathyMobile app for Oral Cancer screening |
| Point-of-care testing | Blood glucose and HbA1cblood pressurespirometryhaemoglobin estimation |
| Sample collection | Cervical (Pap smear) |
| Digital | AI-enabled diagnostic decision supporttelemedicine connectivityspecialist teleradiology reportingdigital health records and referral tracking |
AI-Assisted Screening with Specialist Validation
AI interpretation is applied to four of the nine conditions, and to no others. Stating the boundary plainly is deliberate: the strength of this model is specialist validation, not the breadth of the AI claim.
Read with AI support, validated by a specialist
| Condition | AI-assisted screening | Specialist validation |
|---|---|---|
| Breast cancer | Digital mammography with AI-assisted interpretation | Qualified radiologists |
| Oral cancer | Visual examination with AI-based clinical decision support | Dental specialists |
| Diabetic retinopathy | Retinal imaging with AI-assisted interpretation | Ophthalmologists |
| Tuberculosis | Digital chest X-ray with AI-assisted interpretation | Qualified radiologists |
Laboratory and point-of-care tests,
reviewed by a clinician
| Condition | Screening method | Reviewed by |
|---|---|---|
| Cervical cancer | Pap smear collection and laboratory analysis | Pathologists and gynaecologists |
| Diabetes | Point-of-care blood glucose | Physicians |
| Hypertension | Blood pressure measurement | Physicians |
| COPD | Spirometry | Physicians |
| Anaemia | Point-of-care haemoglobin estimation | Physicians |
AI assists; specialists decide.
An Institutional Ecosystem Designed for Scale
Public health
Partner
Government health systems
Role
Primary care infrastructure, frontline health workers and treatment pathways.Clinical coordination
Partner
Telerad Foundation, Bengaluru hub
Role
Centralised telemedicine, teleradiology, quality assurance and rapid clinical review.Technology
Partner
Indian Institute of Science, Bengaluru and Telerad Foundation
Role
AI-enabled oral cancer screening by IISC; breast cancer and TB risk assessment tools by Telerad Foundation.Clinical
Partner
Kidwai Memorial Institute of Oncology, Bengaluru
Role
Referral integration, specialist support and clinical validation for the cancer components.The unit works alongside government health facilities, district administrations and frontline health workers — strengthening public health infrastructure rather than replacing it.
How the Programme Works
The first deployment is Ramanagara district, Karnataka — 14 primary health centres serving a population of 4,20,000. The unit is stationed at each PHC until the screening target for that catchment is met, then moves on. The next district is chosen once Ramanagara is complete.
Operations
- Deployment rosters developed with NHM and District Health Officers, aligned to local screening priorities.
- The unit visits PHCs, CHCs and government facilities for defined deployment periods.
- Beneficiaries are mobilised through ASHAs, ANMs, self-help groups, local institutions and district health teams, supported by community awareness campaigns.
- Individuals receive services based on age, risk factors, medical history and clinical assessment — nobody is screened for a condition irrelevant to them.
- Digital reporting aligned to NPCDCS, NTEP, Nikshay and Anaemia Mukt Bharat requirements.
Who receives what
The NCD and anaemia components change the programme’s reach among men, who previously received two of the four services offered.| Women | Men | |
|---|---|---|
| Cancer | Breast, cervical, oral | Oral |
| Tuberculosis | Yes | Yes |
| NCDs | All four | All four |
| Anaemia | Yes | No |
Referral and Follow-Up
Screening only counts if it leads somewhere. Individuals requiring further investigation or treatment are linked to government facilities through structured referral pathways, supported by patient navigation, teleconsultation and follow-up until treatment begins.
All operational costs up to and including the pre-referral stage are borne entirely by Telerad Foundation and its supporting partners. This is a non-financial partnership with the Government.
Expected Impact
Figures below are modelled from the deployment plan: nine screening stations running at full capacity, 40 individuals per field day, and 283 operating days a year after Sundays, second and fourth Saturdays and Karnataka government holidays.
First deployment — Ramanagara district
| Ramanagara | |
|---|---|
| Primary health centres | 14 |
| Population Access | 4,20,000 |
| Eligible Population (Adults aged 30-65) | 1,55,400 |
| Individuals screened | 15,540 |
| Screening examinations | 1,14,996 |
| Examinations per individual | 7.4 (Female: 8.2; Male: 5.2) |
One visit, 7.4 screenings. That is the core of the proposition: a person who would otherwise make several separate journeys on several separate days is screened for nine conditions in a single morning.
Annual capacity of one unit
| Per year | Over five years | |
|---|---|---|
| Individuals screened | 11,320 | 56,600 |
| Screening examinations | 83,880 | 4,19,400 |
Figures represent screening examinations. Individuals receive multiple services in a single visit, which is why the two rows differ by a factor of more than seven.
Station throughput
| Station | Per day | Who receives it |
|---|---|---|
| Cervical cancer (Pap smear) | 30 | Every woman who attends |
| Mammography | 30 | Women aged 40–65 |
| Oral cancer | 40 | Every attendee |
| Tuberculosis | 40 | Every attendee |
| Diabetes | 40 | Every attendee |
| Hypertension | 40 | Every attendee |
| COPD | 40 | Every attendee |
| Anaemia | 30 | Women aged 30–49 |
| Diabetic retinopathy | 6 | Only those found diabetic |
Coverage
Running every station at full capacity means different groups are covered at different rates. Stating this openly is deliberate — a single blended uptake figure would conceal a wide spread.
| Group | Screened in Ramanagara | Eligible in district | Coverage |
|---|---|---|---|
| Women aged 40–49 | 11,655 | 23,940 | 48.7% |
| Men aged 30–65 | 3,885 | 75,600 | 5.1% |
| All adults aged 30–65 | 15,540 | 1,55,400 | 10.0% |
Beyond the numbers
The programme also aims to strengthen community awareness, promote preventive health-seeking behaviour, facilitate earlier diagnosis, improve treatment outcomes, and demonstrate how AI, mobile diagnostics and specialist networks can be integrated with public health systems to raise population-level screening coverage.
Partner With Us
The Sanjeevani AI Mobile Health Unit has received seed funding from our Trustees for vehicle procurement, fabrication, medical equipment deployment, insurance and statutory compliance. We invite CSR partners, philanthropic foundations, healthcare institutions and individual donors to support programme operations and service delivery.
| Contribution | Individuals reached |
|---|---|
| ₹4,200 | 1 |
| ₹4.2 lakh | 100 |
| ₹42 lakh | 1,000 |
| ₹4.2 crore | 10,000 |
Each tier is an exact multiple of the ₹4,200 unit cost, which covers screening across all nine conditions, specialist review, and referral and follow-up support. Contributions also fund community mobilisation, digital reporting, programme monitoring and impact measurement.
