Breaking News
January 21, 2019 - Researchers uncover specific microbial signatures of intestinal disease
January 21, 2019 - Plan Your Plate | NIH News in Health
January 21, 2019 - Fecal occult blood test may improve CRC outcomes in some
January 21, 2019 - Mount Sinai joins with Paradigm and ReqMed to repurpose drug for treatment of MPS
January 21, 2019 - FDA Advisory Committee Votes on Zynquista (sotagliflozin) as Treatment for Adults with Type 1 Diabetes
January 21, 2019 - The causes and complications of snoring
January 21, 2019 - Placenta adapts and compensates when pregnant mothers have poor diets or low oxygen
January 21, 2019 - New implant could restore the transmission of electrical signals in injured central nervous system
January 21, 2019 - Rapid-acting fentanyl test strips found to be effective at reducing overdose risk
January 21, 2019 - Coronary Artery Calcium May Help Predict CVD in South Asians
January 21, 2019 - The mystery of the super-ager
January 21, 2019 - Scientists develop smart microrobots that can change shape depending on their surroundings
January 21, 2019 - Keep Moving to Keep Brain Sharp in Old Age
January 21, 2019 - Despite progress, gay fathers and their children still structurally stigmatized
January 21, 2019 - New drug for treating liver parasites in vivax malaria
January 21, 2019 - Merck recognized with 2018 Life Science Industry Award for best use of social media
January 21, 2019 - Coeur Wallis equips the canton of Valais with 260 SCHILLER defibrillators
January 21, 2019 - Scientists propose quick and pain-free method for diagnosing kidney cancer
January 21, 2019 - Signs of memory loss could point to hearing issues
January 21, 2019 - HeartFlow Analysis shows highest diagnostic performance for detecting coronary artery disease
January 21, 2019 - How Much Caffeine is Too Much?
January 21, 2019 - Take a timeout before you force your child to apologize
January 21, 2019 - Scientists design two AI algorithms to improve early detection of cognitive impairment
January 21, 2019 - Novel therapy for children with chronic hormone deficiency provides lifeline for parents
January 21, 2019 - Bioethicists call for oversight of poorly regulated, consumer-grade neurotechnology products
January 21, 2019 - Study shows hereditary hemochromatosis behind many cancers and joint diseases
January 21, 2019 - Short bouts of stairclimbing throughout the day can improve cardiovascular health
January 20, 2019 - Liver Transplant Survival May Improve With Race Matching
January 20, 2019 - Study implicates hyperactive immune system in aging brain disorders
January 20, 2019 - Cancer Diagnosis May Quadruple Suicide Risk
January 20, 2019 - Parkinson’s disease experts devise a roadmap
January 20, 2019 - Research brings new hope to treating degenerative brain diseases
January 20, 2019 - Scientists pinpoint a set of molecules that wire the body weight center of the brain
January 20, 2019 - Researchers get close to developing elusive blood test for Alzheimer’s disease
January 20, 2019 - UCLA researchers demonstrate new technique to develop cancer-fighting T cells
January 20, 2019 - Researchers discover how cancer cells avoid genetic meltdown
January 20, 2019 - Exercise makes even the ‘still overweight’ healthier: study
January 20, 2019 - University of Utah to establish first-of-its-kind dark sky studies minor in the US
January 20, 2019 - School-based nutritional programs reduce student obesity
January 20, 2019 - Improved maternity care practices in the southern U.S. reduce racial inequities in breastfeeding
January 20, 2019 - New enzyme biomarker test indicates diseases and bacterial contamination
January 20, 2019 - Republican and Democratic governors have different visions to transform health care, say researchers
January 20, 2019 - Researchers discover that spin flips happen in only half a picosecond in the course of a chemical reaction
January 20, 2019 - Suicide Risk Up More Than Fourfold for Cancer Patients
January 20, 2019 - Doctors find 122 nails in Ethiopian’s stomach
January 20, 2019 - UV disinfection technology eliminates up to 97.7% of pathogens in operating rooms
January 20, 2019 - Researchers discover mechanism which drives leukemia cell growth
January 20, 2019 - AHA: Infection as a Baby Led to Heart Valve Surgery for Teen
January 20, 2019 - Injection improves vision in a form of childhood blindness
January 20, 2019 - Multiple sclerosis therapies delay progression of disability
January 20, 2019 - New study finds infrequent helmet use among bike share riders
January 20, 2019 - Clearing up information about corneal dystrophies
January 20, 2019 - Researchers describe new behavior in energy metabolism that refutes existing evidence
January 20, 2019 - New study takes first step toward treating endometriosis
January 20, 2019 - Researchers find how GREB1 gene promotes resistance to prostate cancer treatments
January 20, 2019 - Replacing Sitting Time With Activity Lowers Mortality Risk
January 20, 2019 - A simple, inexpensive intervention makes birth safer for moms and babies in parts of Africa
January 19, 2019 - New anti-inflammatory compound acts as ‘surge protector’ to reduce cancer growth
January 19, 2019 - Significant flaws found in recently released forensic software
January 19, 2019 - New Leash on Life? Staying Slim Keeps Pooches Happy, Healthy
January 19, 2019 - Men and women remember pain differently
January 19, 2019 - Rising air pollution linked with increased ER visits for breathing problems
January 19, 2019 - Study uses local data to model food consumption patterns among Seattle residents
January 19, 2019 - The brain’s cerebellum plays role in controlling reward and social behaviors, study shows
January 19, 2019 - Relationship between nurse work environment and patient safety
January 19, 2019 - Pioneering surgery restores movement to children paralyzed by acute flaccid myelitis
January 19, 2019 - Genetic variants linked with risk tolerance and risky behaviors
January 19, 2019 - New research provides better understanding of our early human ancestors
January 19, 2019 - First-ever tailored reporting guidance to improve patient care and outcomes
January 19, 2019 - 4.6 percent of Massachusetts residents have opioid use disorder
January 19, 2019 - New study suggests vital exhaustion as risk factor for dementia
January 19, 2019 - New antibiotic discovery heralds breakthrough in the fight against drug-resistant bacteria
January 19, 2019 - Ural Federal University scientists synthesize a group of multi-purpose fluorophores
January 19, 2019 - Researchers identify new therapeutic target in the fight against chronic liver diseases
January 19, 2019 - Preparation, characterization of Soyasapogenol B loaded onto functionalized MWCNTs
January 19, 2019 - FDA Approves Ontruzant (trastuzumab-dttb), a Biosimilar to Herceptin
January 19, 2019 - Tobacco use linked with higher use of opioids and sedatives
January 19, 2019 - Study delves deeper into developmental dyslexia
January 19, 2019 - Anti-vaccination movement one of the top health threats in 2019 says WHO
January 19, 2019 - Newly developed risk score more effective at identifying type 1 diabetes
New AI algorithm helps predict medication response in patients with complex mood disorder

New AI algorithm helps predict medication response in patients with complex mood disorder

image_pdfDownload PDFimage_print

Mood disorders like major depressive disorder (MDD) and bipolar disorder are often complex and hard to diagnose, especially among youth when the illness is just evolving. This can make decisions about medication difficult. In a collaborative study by Lawson Health Research Institute, The Mind Research Network and Brainnetome Center, researchers have developed an artificial intelligence (AI) algorithm that analyzes brain scans to better classify illness in patients with a complex mood disorder and help predict their response to medication.

The full study included 78 emerging adult patients from mental health programs at London Health Sciences Centre (LHSC), primarily from the First Episode Mood and Anxiety Program (FEMAP). The first part of the study involved 66 patients who had already completed treatment for a clear diagnosis of either MDD or bipolar type I (bipolar I), which is a form of bipolar disorder that features full manic episodes, as well as an additional 33 research participants with no history of mental illness. Each individual participated in scanning to examine different brain networks using Lawson’s functional magnetic resonance imaging (fMRI) capabilities at St. Joseph’s Health Care London.

The research team analyzed and compared the scans of those with MDD, bipolar I and no history of mental illness, and found the three groups differed in particular brain networks. These included regions in the default mode network, a set of regions thought to be important for self-reflection, as well as in the thalamus, a ‘gateway’ that connects multiple cortical regions and helps control arousal and alertness.

The data was used by researchers at The Mind Research Network to develop an AI algorithm that uses machine learning to examine fMRI scans to classify whether a patient has MDD or bipolar I. When tested against the research participants with a known diagnosis, the algorithm correctly classified their illness with 92.4 per cent accuracy.

The research team then performed imaging with 12 additional participants with complex mood disorders for whom a diagnosis was not clear. They used the algorithm to study a participant’s brain function to predict his or her diagnosis and, more importantly, examined the participant’s response to medication.

“Antidepressants are the gold standard pharmaceutical therapy for MDD while mood stabilizers are the gold standard for bipolar I,” says Dr. Elizabeth Osuch, a clinician-scientist at Lawson, medical director at FEMAP and co-lead investigator on the study. “But it becomes difficult to predict which medication will work in patients with complex mood disorders when a diagnosis is not clear. Will they respond better to an antidepressant or to a mood stabilizer?”

The research team hypothesized that participants classified by the algorithm as having MDD would respond to antidepressants while those classified as having bipolar I would respond to mood stabilizers. When tested with the complex patients, 11 out of 12 responded to the medication predicted by the algorithm.

“This study takes a major step towards finding a biomarker of medication response in emerging adults with complex mood disorders,” says Dr. Osuch. “It also suggests that we may one day have an objective measure of psychiatric illness through brain imaging that would make diagnosis faster, more effective and more consistent across health care providers.”

Psychiatrists currently make a diagnosis based on the history and behavior of a patient. Medication decisions are based on that diagnosis. “This can be difficult with complex mood disorders and in the early course of an illness when symptoms may be less well-defined,” says Dr. Osuch. “Patients may also have more than one diagnosis, such as a combination of a mood disorder and a substance abuse disorder, further complicating diagnosis. Having a biological test or procedure to identify what class of medication a patient will respond to would significantly advance the field of psychiatry.”

Source:

https://www.lawsonresearch.ca/machine-learning-could-predict-medication-response-patients-complex-mood-disorders

Tagged with:

About author

Related Articles