Health Life

Researchers use artificial intelligence tools to predict loneliness

Credit: CC0 Public Domain

For the past couple of decades, there has been a loneliness pandemic, marked by rising rates of suicides and opioid use, lost productivity, increased health care costs and rising mortality. The COVID-19 pandemic, with its associated social distancing and lockdowns, have only made things worse, say experts.

Accurately assessing the breadth and depth of societal loneliness is daunting, limited by available tools, such as self-reports. In a new proof-of-concept paper, published online September 24, 2020 in the American Journal of Geriatric Psychiatry, a team led by researchers at University of California San Diego School of Medicine used artificial intelligence technologies to analyze patterns (NLP) to discern degrees of loneliness in older adults.

“Most studies use either a direct question of ‘ how often do you feel lonely,’ which can lead to biased responses due to stigma associated with loneliness or the UCLA Loneliness Scale which does not explicitly use the word ‘lonely,'” said senior author Ellen Lee, MD, assistant professor of psychiatry at UC San Diego School of Medicine. “For this project, we used natural language processing or NLP, an unbiased quantitative assessment of expressed emotion and sentiment, in concert with the usual loneliness measurement tools.”

In recent years, numerous studies have documented rising rates of loneliness in various populations of people, particularly those most vulnerable, such as older adults. For example, a UC San Diego study published earlier this year found that 85 percent of residents living in an independent senior housing community reported moderate to severe levels of loneliness.

The new study also focused on independent senior living residents: 80 participants aged 66 to 94, with a mean age of 83 years. But, rather than simply asking and documenting answers to questions from the UCLA Loneliness Scale, participants were also interviewed

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Tips for supporting loved ones with alcohol use disorders

The support of friends and family is important in the journey to recovery from alcohol use disorder (AUD). The National Institute on Alcohol Abuse and Alcoholism, which leads research on AUD, shares information on how you can help a loved one.

Participate. Seek a program to help you support your loved one. Programs like Al-Anon Family Groups or Adult Children of Alcoholics can help people understand the disorder, what they can do to help, and their role in a loved one’s recovery.

Be patient. Changing deep habits is hard, takes time, and may require repeated efforts. Practice patience with your loved one and understand that overcoming this disorder is not easy or quick.

Celebrate successes. Pay attention to your loved one during the recovery process. Appreciate successes, no matter how small.

Take care of yourself. Caring for a person who has difficulties with alcohol can be stressful. Ask for support from friends, family, support groups, or mental health professionals. This is especially important if you feel depressed or anxious. Remember that your loved one is ultimately responsible for managing this illness.

For additional support, check out the NIAAA Alcohol Treatment Navigator®.

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Health Life

Deep learning helps explore the structural and strategic bases of autism?

Visualization of logics of classification learned by recurrent attention model (RAM). Credit: The Korea Advanced Institute of Science and Technology (KAIST)

Psychiatrists typically diagnose autism spectrum disorders (ASD) by observing a person’s behavior and by leaning on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), widely considered the ‘bible’ of mental health diagnosis.

However, there are substantial differences amongst individuals on the spectrum and a great deal remains unknown by science about the causes of autism, or even what autism is. As a result, an accurate diagnosis of ASD and a prognosis prediction for patients can be extremely difficult.

But what if (AI) could help? Deep learning, a type of AI, deploys based on the to recognize patterns in a way that is akin to, and in some cases can surpass, human ability. The technique, or rather suite of techniques, has enjoyed remarkable success in recent years in fields as diverse as voice recognition, translation, autonomous vehicles, and drug discovery.

A group of researchers from KAIST in collaboration with the YonseiUniversity College of Medicine has applied these to autism diagnosis. Their findings were published on August 14 in the journal IEEE Access.

Magnetic resonance imaging (MRI) scans of brains of people known to have autism have been used by researchers and clinicians to try to identify structures of the brain they believed were associated with ASD. These researchers have achieved considerable success in identifying abnormal gray and white matter volume and irregularities in cerebral cortex activation and connections as being associated with the condition.

These findings have subsequently been deployed in studies attempting more consistent diagnoses of patients than has been achieved via psychiatrist observations during counseling sessions. While such studies have reported high levels of diagnostic accuracy,

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Monoclonal Antibodies – National Cancer Institute

Monoclonal antibodies can cause side effects, which can differ from person to person. The ones you may have and how they make you feel will depend on many factors, such as how healthy you are before treatment, your type of cancer, how advanced it is, the type of monoclonal antibody you are receiving, and the dose.

Doctors and nurses cannot know for sure when or if side effects will occur or how serious they will be. So, it is important to know which signs to look for and what to do if you start to have problems.

Like most types of immunotherapy, monoclonal antibodies can cause skin reactions at the needle site and flu-like symptoms.

Needle site reactions include:

  • Pain
  • Swelling
  • Soreness
  • Redness
  • Itchiness
  • Rash

Learn more about skin changes caused by cancer treatment.

Flu-like symptoms include:

  • Chills
  • Fatigue
  • Fever
  • Muscle aches and pains
  • Nausea
  • Vomiting
  • Diarrhea

Learn more about flu-like symptoms caused by cancer treatment.

Monoclonal antibodies can also cause:

  • Mouth and skin sores that can lead to serious infections
  • High blood pressure
  • Congestive heart failure
  • Heart attacks
  • Inflammatory lung disease

Monoclonal antibodies can cause mild to severe allergic reactions while you are receiving the drug. In rare cases, the reaction is severe enough to cause death.

Some monoclonal antibodies can also cause capillary leak syndrome. This syndrome causes fluid and proteins to leak out of tiny blood vessels and flow into surrounding tissues, resulting in dangerously low blood pressure. Capillary leak syndrome may lead to multiple organ failure and shock.

Cytokine release syndrome can sometimes occur with monoclonal antibodies, but it is often mild. Cytokines are immune substances that have many different functions in the body, and a sudden increase in their levels can cause:

  • Fever
  • Nausea
  • Headache
  • Rash
  • Rapid heartbeat
  • Low blood pressure
  • Trouble breathing