A drone hovers over Tacuarembó hospital in Uruguay, carrying its precious cargo: breast milk intended for children in remote parts of the country.
But these children need breast milk throughout their first six months, if not longer, to prevent malnutrition and other illnesses that are prevalent in rural Tacuarembó. Ground transport isn't quick or reliable enough to meet this goal. It can take several hours, during which the milk may spoil due to a lack of refrigeration.
The battery-powered drones have been the difference-maker. The project to develop them, financed by the UNICEF Innovation Fund, is the first of its kind in Latin America. To Castelli, it's nothing short of a revolution. Tacuarembó Hospital, along with three rural clinics in the most impoverished part of Uruguay, are its leaders.
"This marks the first occasion when the public health system has been directly impacted [by our technology]," says Sebastián Macías, the CEO and co-founder of Cielum, an engineer at the University Republic, which collaborated on the technology with a Uruguayan company called Cielum and a Swiss company, Rigitech.
The drone can achieve a top speed of up to 68 miles per hour, is capable of flying in light rain, and can withstand winds of up to 30 miles per hour at a maximum altitude of 120 meters.
"We have succeeded in embracing the mothers from rural areas who were previously slipping through the cracks of the system," says Ferreira, the hospital director. He envisions an expansion of the service so it can improve health for children in other rural areas.
Nurses load the drone for breast milk delivery.
Sebastián Macías - Cielum
The star aircraft
The drone, which costs approximately $70,000, was specifically designed for the transportation of biological materials. Constructed from carbon fiber, it's three meters wide, two meters long and weighs 42 pounds when fully loaded. Additionally, it is equipped with a ballistic parachute to ensure a safe descent in case the technology fails in midair. Furthermore, it can achieve a top speed of 68 miles per hour, fly in light rain, and withstand winds of 30 miles per hour at a height of 120 meters.
Inside, the drones feature three refrigerated compartments that maintain a stable temperature and adhere to the United Nations’ standards for transporting perishable products. These compartments accommodate four gallons or 6.5 pounds of cargo. According to Macías, that's more than sufficient to carry a week’s worth of milk for one infant on just two flights, or 3.3 pounds of blood samples collected in a rural clinic.
“From an energy perspective, it serves as an efficient mode of transportation and helps reduce the carbon emissions associated with using an ambulance,” said Macías. Plus, the ambulance can remain available in the town.
Macías, who has led software development for the drone, and three other technicians have been trained to operate it. They ensure that the drone stays on course, monitor weather conditions and implement emergency changes when needed. The software displays the in-flight positions of the drones in relation to other aircraft. All agricultural planes in the region receive notification about the drone's flight path, departure and arrival times, and current location.
The future: doubling the drone's reach
Forty-five days after its inaugural flight, the drone is now making five flights per week. It serves two routes: 34 miles to Curtina and 31 miles to Tambores. The drone reaches Curtina in 50 minutes while ambulances take double that time, partly due to the subpar road conditions. Pueblo Ansina, located 40 miles from the state capital, will soon be introduced as the third destination.
Overall, the drone’s schedule is expected to become much busier, with plans to accomplish 20 weekly flights by the end of October and over 30 in 2024. Given the drone’s speed, Macías is contemplating using it to transport cancer medications as well.
“When it comes to using drones to save lives, for us, the sky is not the limit," says Ciro Ferreira, Tacuarembó hospital director.
In future trips to clinics in San Gregorio de Polanco and Caraguatá, the drone will be pushed to the limit. At these locations, a battery change will be necessary, but it's worth it. The route will cover up to 10 rural Tacuarembó clinics plus one hospital outside Tacuarembó, in Rivera, close to the border with Brazil. Currently, because of a shortage of ambulances, the delivery of pasteurized breast milk to Rivera only occurs every 15 days.
“The expansion to Rivera will include 100,000 more inhabitants, doubling the healthcare reach,” said Ferreira, the director of the Tacuarembó Hospital. In itself, Ferreira's hospital serves the medical needs of 500,000 people as one of the largest in Uruguay's interior.
Alejandro Del Estal, an aeronautical engineer at Rigitech, traveled from Europe to Tacuarembó to oversee the construction of the vertiports – the defined areas that can support drones’ take-off and landing – and the first flights. He pointed out that once the flight network between hospitals and rural polyclinics is complete in Uruguay, it will rank among the five most extensive drone routes in the world for any activity, including healthcare and commercial uses.
Cielum is already working on the long-term sustainability of the project. The aim is to have more drones operating in other rural regions in the western and northern parts of the country. The company has received inquiries from Argentina and Colombia, but, as Macías pointed out, they are exercising caution when making commitments. Expansion will depend on the development of each country’s regulations for airspace use.
For Ferreira, the advantages in Uruguay are evident: "This approach enables us to bridge the geographical gap, enhance healthcare accessibility, and reduce the time required for diagnosing and treating rural inhabitants, all without the necessity of them traveling to the hospital,” he says. "When it comes to using drones to save lives, for us, the sky is not the limit."
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.