Artificial intelligence-powered handheld devices are now bringing breast and cervical cancer screening to primary health centers in rural India, eliminating barriers like cost, distance, and lack of awareness that have historically prevented early detection. Over 33,000 women across Telangana and Andhra Pradesh have been screened using these portable devices, which flag signs of disease without requiring expensive mammography machines or specialized infrastructure.

Why Are Handheld AI Screening Devices Needed in Rural Healthcare?

Traditional breast cancer screening relies on mammography machines, which are expensive, require dedicated infrastructure, and need trained radiographers. In rural areas, women often delay seeking care because of cost, distance, lack of awareness, or stigma, allowing disease to progress undetected. The new handheld devices attempt to solve this problem by providing initial screening at the point of care, saving women an unnecessary trip to a cancer hospital or specialized oncology center.

At Alwal Primary Health Centre in Hyderabad's Medchal-Malkajgiri district, nurses are now using two AI-powered devices: iBreastExam for breast screening and cervAIcal for cervical screening. These devices were deployed under a program implemented by Mahita Foundation with support from Indian Oil Corporation's Corporate Social Responsibility initiative.

How Do These AI Screening Devices Actually Work?

• Breast Screening Device (iBreastExam): The handheld device contains 648 capacitive pressure sensors that record differences in tissue elasticity roughly 20 times per second. Healthy and abnormal tissue respond differently to gentle pressure, and the sensors convert those differences into digital signals that the software processes to flag patterns diverging from normal tissue. The examination takes between 5 and 10 minutes, involves no radiation exposure, and is completely painless.
• Cervical Screening Device (cervAIcal): This portable digital colposcope clips onto a smartphone. The cervix is first cleaned with normal saline and photographed, then acetic acid is applied and another photograph is taken after 1 to 2 minutes. If abnormality exists, the tissue color changes, which the AI detects.
• Offline Operation: Both devices pair with a smartphone via Bluetooth and operate completely offline. The device battery lasts a full day of screenings after roughly 6 hours of charging, making them practical for resource-limited settings.

The devices are designed to identify potential signs of disease rather than diagnose cancer. When the software detects suspicious changes in tissue, the woman is referred to a higher center for mammography, biopsy, or specialist consultation. If screening is normal, she returns home reassured.

What Real-World Results Are Emerging From These Screenings?

One compelling case involved Shahnaz Begum, an Auxiliary Nurse Midwife at Alwal Primary Health Centre with nearly two decades of experience. She had noticed a small lump in her right breast nearly 15 years earlier but had not pursued it because it never increased in size. About 8 months before the screening program launched, the lump grew and became raised, making her suspicious.

"When the device was introduced at our PHC, all the staff members, including ASHA workers and ANMs, underwent screening first. I also got myself screened. During the examination, the device detected a lump in my right breast," Shahnaz recalled.

Shahnaz Begum, Auxiliary Nurse Midwife at Alwal Primary Health Centre

The screening identified an abnormality, but diagnosis still required a biopsy. A private hospital quoted between 15,000 and 20,000 Indian rupees for further investigations, which was beyond her means. Through referrals, she was able to undergo surgery free of cost. The diagnosis confirmed Grade I breast cancer. Because it was detected early, she underwent surgery followed by 3 months of treatment and now returns for follow-up every 6 months while continuing to work at the PHC.

"We never expected that such a small handheld device at a Primary Health Centre could help detect something like this. When we tell women that we have undergone the same screening ourselves, they become much more comfortable. Sometimes I even tell them my own story. That gives them confidence," Shahnaz explained.

Shahnaz Begum, Auxiliary Nurse Midwife at Alwal Primary Health Centre

How Are Healthcare Workers Building Trust in the Screening Process?

Before the screening program opened to the public, Mahita Foundation deliberately ran it through the primary health center's own staff first, including nurses, Auxiliary Nurse Midwives (ANMs), and ASHA workers (accredited social health activists). This strategy served two purposes: it allowed frontline health workers to understand how the devices work and build confidence in the screening process, and it enabled them to become advocates in their communities.

"We first screened ASHA workers and ANMs. We wanted frontline health workers to understand how the devices work and build confidence in the screening process. They visit households regularly, and when they themselves undergo screening and understand how the devices work, they are better able to explain the process to women in their communities and encourage them to come forward," explained Balchander, who oversees the program's implementation.

Balchander, Program Implementation Overseer, Mahita Foundation

Staff Nurse Pranay Sheela described the practical workflow: before examination, the nurse registers the patient, entering her name, age, and contact details into the mobile application. The size and shape of the breast are then entered, which allows the application to create a digital grid of 9, 16, or 25 sections. Each section is scanned individually, with the application guiding the nurse throughout the examination.

What Broader Challenges Remain in Cancer Biomarker Testing?

While AI-powered screening devices are expanding access to initial detection, a separate challenge exists in the treatment phase: biomarker testing for metastatic breast cancer remains critically low. A real-world analysis of 288 patients with hormone receptor-positive, HER2-negative metastatic breast cancer found that testing of clinically actionable biomarkers ranged from just 17.4% to 27.4% after first-line treatment initiation.

These biomarkers include PIK3CA, ESR1, AKT1, PTEN, and BRCA1/2, which can guide targeted second-line therapies. Testing was not aligned with key clinical milestones: only 9 to 17% of patients received testing at metastatic diagnosis, 6 to 11% at first-line progression, and 6 to 15% during or after subsequent lines of therapy.

"In this contemporary patient cohort, biomarker testing was low and not aligned with the timing of second-line treatment decisions. Low biomarker testing rates continue to represent missed opportunities for identifying tumor-directed targeted therapies and improving outcomes," the researchers concluded.

Researchers, Miami Breast Cancer Conference

The gap between screening innovation and treatment optimization highlights a broader opportunity: as AI tools expand early detection capabilities, healthcare systems must simultaneously improve the infrastructure for biomarker testing to ensure that detected cancers receive the most targeted, effective treatment available.