AI can spot depression via sound of your voice

India -- the sixth most depressed country in the world -- has an estimated 56 million people suffering from depression and 38 million from anxiety disorders, according to a recent report by the World Health Organisation (WHO).

To help identify depression early, scientists have now enhanced a technology that uses Artificial Intelligence (AI) to sift through sound of your voice to gauge whether you are depressed or not.

Computing science researchers  have improved technology for identifying depression through vocal cues.

The study builds on past research that suggests that the timbre of our voice contains information about our mood.

Using standard benchmark data sets, the team developed a methodology that combines several Machine Learning (ML) algorithms to recognize depression more accurately using acoustic cues.

A realistic scenario is to have people use an app that will collect voice samples as they speak naturally.

"The app, running on the user's phone, will recognize and track indicators of mood, such as depression, over time. Much like you have a step counter on your phone, you could have a depression indicator based on your voice as you use the phone," he said.

Depression is ranked by WHO as the single largest contributor to global disability. It is also the major contributor to suicide deaths.

The ultimate goal, said researchers, is to develop meaningful applications from this technology.

Such a tool could prove useful to support work with care providers or to help individuals reflect on their own moods over time.

"This work, developing more accurate detection in standard benchmark data sets, is the first step," he added while presenting the paper recently.

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Novel app may predict hernia risk after abdominal surgery

Researchers have created an app that may predict the likelihood of developing an incisional hernia following an abdominal surgery, using Big Data analytics to potentially help address a problem effects one out of every 8 of these surgical patients.

The team developed the app utilising electronic health records (EHR) to identify the most common risk factors for patients, as well as which surgeries most commonly result in incisional hernias across multiple specialties.

Our tool presents the risk for each case at the point of care, giving surgeons and patients the chance to consider this outcome ahead of time and incorporate data into the decision-making process, said the co-author of the study.

Incisional hernias occur after abdominal surgery at the site of the surgical wound when the contents of the abdomen can push through the muscle.

For the study, the team analysed the EHRs of 29,730 patients undergoing intra-abdominal urological or gynecological surgery between Jan. 2005 and June 2016.

They found more than 1,100 of these patients ended up requiring a second surgery following the primary operation to repair the incision hernias.

Colorectal surgeries were the most common specialty associated with incision hernias, followed by vascular, bariatric and transplant.

The analysis also identified risk factors that made a patient more likely to develop an incisional hernia.

The most common was a history of abdominal surgery, which increased the likelihood in 87.5% of cases. That was followed by a history of smoking and a recent infection 75 % for both. Obesity was also a significant risk, though it was weighted less than other risk factors.

 

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Researchers have created an app that may predict the likelihood of developing an incisional hernia following an abdominal surgery, using Big Data analytics to potentially help address a problem effects one out of every eight of these surgical patients. The team developed the app utilising electronic health records (EHR) to identify the most common risk factors for patients, as well as which surgeries most commonly result in incisional hernias across multiple specialties.

https://www.thehansindia.com/tech/novel-app-may-predict-hernia-risk-after-abdominal-surgery-520910

Researchers have created an app that may predict the likelihood of developing an incisional hernia following an abdominal surgery, using Big Data analytics to potentially help address a problem effects one out of every eight of these surgical patients. The team developed the app utilising electronic health records (EHR) to identify the most common risk factors for patients, as well as which surgeries most commonly result in incisional hernias across multiple specialties.

https://www.thehansindia.com/tech/novel-app-may-predict-hernia-risk-after-abdominal-surgery-520910

Tech can be key in treating congenital heart defects’

A state which lowered child mortality significantly in the past decade, could further the trend by investing in technology to treat congenital heart defects (CHDs), said experts.
 
The head of the Department of Cardiology said India had a huge burden with around 2-2.5 lakh babies born annually suffering from congenital heart defects. Around 80,000 have serious complications but though most of them only require a single corrective surgery to live a normal life, they often have no access to them, he told media-persons here on Friday.
Hospitals also lack technical and human resources to deal with the scale of the burden. “It is only after the mortality rates fell that states began looking at CHDs. We are now operating on pre-term babies but the challenges are huge,” he said.
At the hospital, doctors operated on a 1.8 kg baby born three months before term. The baby was referred to the hospital by doctors. The baby’s father said the baby was diagnosed with a hole in the heart three days after birth, and it enlarged within a week.
Cardiovascular surgeon, who performed the surgery, said since pre-term babies’ tissues are fragile, more care is needed before and during the surgery. He used a 3D printed image of the baby’s heart from the MRI scan to help identify the exact type of lesion and cut the cardiopulmonary bypass time. This reduced the recovery time, the Dr. explained.
The institute’s expertise in paediatric cardiac surgeries led it to develop an app. A professor of Paediatric Cardiology in-charge of MRI and 3D Printing, said the study of 1,100 babies brought to the institute found that safer transport would improve their survival chances. It helped develop an app to provide real time data even as the baby is transported by ambulance. The app will be launched in soon the Dr. said.
The institute has installed a 3D printer which has helped in planning complicated surgeries in other specialities also. 

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This Fantastic New App Can Detect Pancreatic Cancer

Better screening tools for all cancers would be great, but one type in particular where it could have a huge impact is pancreatic cancer. The symptoms of this devastating disease don’t reveal themselves until it’s well advanced, and it carries a five-year survival rate of just 5-9%.
 
Now, scientists have developed an app that could allow people to easily detect pancreatic cancer by simply scanning the white part of the eye for one of the disease’s early tell-tale signs.

One of the early signs of pancreatic cancer is jaundice, which is characterized by yellowing of the skin and eyes as a result of the buildup of a substance in the blood known as bilirubin. However, the trouble with bilirubin buildup, other than the fact that it can be an indication of several diseases, is that it can only be detected by blood tests that doctors won’t administer unless there is already cause for concern.
 
We have already recently seen exciting progress towards a urine test for pancreatic cancer, but this new app would require no bodily fluids at all.

Dubbed Biliscreen, this app uses a smartphone camera along with computer vision algorithms and machine learning to detect increased levels of bilirubin in the white part of the eye, known as the sclera. In adults, the sclera is more sensitive than the skin to elevated bilirubin levels and the team hopes that Biliscreen will be able to detect these changes before they become visible to naked eye, when it’s already too late.   

The senior author of the study, states that “the eyes are a really interesting gateway into the body – tears can tell you how much glucose you have, sclera can tell you how much bilirubin is in your blood. Our question was: Could we capture some of these changes that might lead to earlier detection with a selfie?”
The technology was put to the test in a clinical trial that involved 70 people. The app was used in combination with either a special box made to control light exposure or paper glasses to calibrate color. The team found that it was able to detect causes for concern 89.7% of the time.

It works by using the camera and flash to capture an image of the eye, and then computer vision software to isolate the sclera. The app then assesses the wavelengths of light that are being reflected and absorbed by the sclera, calculating color information, and then uses machine learning algorithms to correlate that with bilirubin levels.

The co-author of the study, explains that “this relatively small initial study shows the technology has promise. Pancreatic cancer is a terrible disease with no effective screening right now. Our goal is to have more people who are unfortunate enough to get pancreatic cancer to be fortunate enough to catch it in time to have surgery that gives them a better chance of survival.”

Now, the team is looking to build on these exciting early results by testing the app on larger groups of people at risk of jaundice and other related conditions. They are also going to try to make the technology more convenient to use, by possibly removing the need for the box or glasses.

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