Small changes in how a person talks could reveal Alzheimer’s earlier
Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.
“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”
When a patient is diagnosed with early-stage breast cancer, having surgery to remove the tumor is considered the standard of care. But what happens when a patient can’t have surgery?
Whether it’s due to high blood pressure, advanced age, heart issues, or other reasons, some breast cancer patients don’t qualify for a lumpectomy—one of the most common treatment options for early-stage breast cancer. A lumpectomy surgically removes the tumor while keeping the patient’s breast intact, while a mastectomy removes the entire breast and nearby lymph nodes.
Fortunately, a new technique called cryoablation is now available for breast cancer patients who either aren’t candidates for surgery or don’t feel comfortable undergoing a surgical procedure. With cryoablation, doctors use an ultrasound or CT scan to locate any tumors inside the patient’s breast. They then insert small, needle-like probes into the patient's breast which create an “ice ball” that surrounds the tumor and kills the cancer cells.
Cryoablation has been used for decades to treat cancers of the kidneys and liver—but only in the past few years have doctors been able to use the procedure to treat breast cancer patients. And while clinical trials have shown that cryoablation works for tumors smaller than 1.5 centimeters, a recent clinical trial at Memorial Sloan Kettering Cancer Center in New York has shown that it can work for larger tumors, too.
In this study, doctors performed cryoablation on patients whose tumors were, on average, 2.5 centimeters. The cryoablation procedure lasted for about 30 minutes, and patients were able to go home on the same day following treatment. Doctors then followed up with the patients after 16 months. In the follow-up, doctors found the recurrence rate for tumors after using cryoablation was only 10 percent.
For patients who don’t qualify for surgery, radiation and hormonal therapy is typically used to treat tumors. However, said Yolanda Brice, M.D., an interventional radiologist at Memorial Sloan Kettering Cancer Center, “when treated with only radiation and hormonal therapy, the tumors will eventually return.” Cryotherapy, Brice said, could be a more effective way to treat cancer for patients who can’t have surgery.
“The fact that we only saw a 10 percent recurrence rate in our study is incredibly promising,” she said.
Few things are more painful than a urinary tract infection (UTI). Common in men and women, these infections account for more than 8 million trips to the doctor each year and can cause an array of uncomfortable symptoms, from a burning feeling during urination to fever, vomiting, and chills. For an unlucky few, UTIs can be chronic—meaning that, despite treatment, they just keep coming back.
But new research, presented at the European Association of Urology (EAU) Congress in Paris this week, brings some hope to people who suffer from UTIs.
Clinicians from the Royal Berkshire Hospital presented the results of a long-term, nine-year clinical trial where 89 men and women who suffered from recurrent UTIs were given an oral vaccine called MV140, designed to prevent the infections. Every day for three months, the participants were given two sprays of the vaccine (flavored to taste like pineapple) and then followed over the course of nine years. Clinicians analyzed medical records and asked the study participants about symptoms to check whether any experienced UTIs or had any adverse reactions from taking the vaccine.
The results showed that across nine years, 48 of the participants (about 54%) remained completely infection-free. On average, the study participants remained infection free for 54.7 months—four and a half years.
“While we need to be pragmatic, this vaccine is a potential breakthrough in preventing UTIs and could offer a safe and effective alternative to conventional treatments,” said Gernot Bonita, Professor of Urology at the Alta Bro Medical Centre for Urology in Switzerland, who is also the EAU Chairman of Guidelines on Urological Infections.
The news comes as a relief not only for people who suffer chronic UTIs, but also to doctors who have seen an uptick in antibiotic-resistant UTIs in the past several years. Because UTIs usually require antibiotics, patients run the risk of developing a resistance to the antibiotics, making infections more difficult to treat. A preventative vaccine could mean less infections, less antibiotics, and less drug resistance overall.
“Many of our participants told us that having the vaccine restored their quality of life,” said Dr. Bob Yang, Consultant Urologist at the Royal Berkshire NHS Foundation Trust, who helped lead the research. “While we’re yet to look at the effect of this vaccine in different patient groups, this follow-up data suggests it could be a game-changer for UTI prevention if it’s offered widely, reducing the need for antibiotic treatments.”