New Study Will Confirm The Efficiency Of Depression Treatment

Psychiatry || Treatment of Depression

New Study Will Confirm The Efficiency Of Depression Treatment

Experts are beginning to implement AI and Imaging to discover the causes, varieties, and possible treatments of depression.

The question that usually surfaces during every examination, which might take a while to fully comprehend is “how are you feeling?”. It’s a question being asked by your physician to know if you are depressed. Or probably you are already aware of your depressed state and have booked an appointment to get help.  In any case, the painful or depressing truth is that physicians only have very few solutions to recommend without any idea if it will be effective.

Online Psychiatry Miami – Is provided by Psychiatry Concierge which assist in treating depression.

This includes:

Cognitive-behavioral therapy (CBT) such as having a conversation with someone.

Using medication which is usually an SNRI or SSRI medication.

Vox indicated that these methods are not usually very efficient as improvements are only observed in 40% of patients. Leanne Maree Williams, a Stanford professor informed Vox that the study is currently just speculation, and to be realistic, there is nothing worse than the current situation which is a major issue. The NIH estimated that in 2015, about 16.1 million adults in America have suffered from a minimum of one incident of depression.

Depression is considered by the Mayo Clinic as a mood disorder that creates a consistent feeling of loss of interest and sadness. More than this, it is simply a combination of different conditions that have no universal and effective treatment.



This is what it implies: On a diagnosis of depression in a  patient, at least five of these requirements are reported by the Diagnostic and Statistical Manual of Mental Disorders.

  1. Irritable or depressed mood the entire day, which occurs almost every day as described by the subjective report (feeling of sadness or emptiness) or as observed by other people (such as a teary face).
  2. Loss of interest in fun and pleasure in almost all activities the entire day.
  3. Major weight (5%) or appetite change.
  4. Changes in sleep routines such as hypersomnia or insomnia.
  5. Activity changes such as retardation or Psychomotor agitation.
  6. Tiredness and energy loss.
  7. A feeling of worthlessness or guilt.
  8. Focus: Low capacity of being focused or decisive.
  9. Suicidal thoughts or plans.

All these symptoms are very unlikely to have a similar cause, but different biological triggers can be the source of similar symptoms. Conor Liston, the research psychiatrist at Weill Cornell Medical College indicated that there are different kinds of depression but the similar feeling of disappointment and frustration shared by himself and many psychiatrists is that many of their works are experimental as well as the inability to get sufficient data useful for improving their decision-making process.

Liston is currently involved in a project of discovering the subcategories of depression with the use of machine learning and fMRI scans. About 1,118 volunteers were screened by Liston and a team of Canadian and American researchers in a state of rest, which is an enormous sample for the study. The fMRI monitored the brains of these patients while performing no specific activity searching for two or more regions that are simultaneously active.  The strength of this correlation will determine the strength of these regions. Evaluating the activity of this resting state will help to discover the “default” connection of each patient. 458 of the 1,118 of these respondents were found to be depressive.

The team programmed the AI to examine the patients for depressions on the basis of their connections and the computer was 84% effective.

Subsequently, the scan results from the depressive respondents were analyzed by the computer to determine or discover any brain activity that indicates depression. Four depression-related subcategories of activity were discovered, known as “biotypes” which explains the connection between the medial prefrontal cortex and other regions. The medial prefrontal cortex is responsible for personal thoughts.

The four biotypes include:

Biotype 1 is connected with insomnia, anxiety, and fatigue.

Biotype 2 is connected with low energy and tiredness.

Biotype 3 is connected with the incapacity to experience pleasure together with slurring or slow speech and movement.

Biotype 4 is connected with sleeplessness and anxiety as well as the inability of experiencing pleasure.

Liston was fascinated about observing the possibilities of an effective treatment that is different from biotypes and carried out Transcranial Magnetic Stimulation (TNS) on the depressed individuals and the treatment is non-invasive, which physicians might have to employ whenever therapies and conversations are no longer effective.

He discovered that TMS has a 3 times higher chance of being effective in Biotype 1 patients than Biotype 2 and Biotype 4 patients.

Machine learning and fMRI were used in a completely different direction by another team to address the problem and also ended up with similar outcomes even though they had different Biotypes than that of Liston. fMRI was used to scan the resting condition of 122 depressive patients who received treatments for about 12 weeks through medications (SNRIs and SSRIs) and CBT. After the test, patients were asked if their depression has been effectively addressed, in which the scientists had to use the fMRI to analyze the existence of brain activity patterns that confirm the successful cases.


A member of this team, Psychologist W. Edward Craighead informs Vox that brain types that respond to psychotherapy are the regions with a stronger connectivity trait between the frontal region of the brain that is responsible for speech, thoughts, solving problems and so on, with other regions of the brain.  Alternatively, individuals with lower connection with this region usually end up responding to treatment.

According to statistics, patients with very strong connections have about 76% of the possibility of responding to CBT treatment and about 5 to 10% possibility of responding to medication. The discovery was a reverse for patients with lower connections. They have a 50% possibility of responding to medications and a 5% possibility of responding to CBT treatment. 58 respondents were discovered to respond to treatments. The sample size for the study was relatively small and requires additional research to confirm the discoveries.

Either way, these studies portray the start of introducing fMRIs and AI to combat the symptoms of depression and create advanced treatments that effectively combat the stubborn and life eroding health condition.

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