Precision Medicine

Various iterations of AI “hold tremendous promise” to help personalize counseling for individuals grieving the loss of a loved one. 

Emergency physicians have a tough time identifying patients who have Crohn’s disease and truly need a CT scan to pinpoint the cause of acute abdominal distress.

Comparing four methods for predicting septic shock in children hospitalized with sepsis, Johns Hopkins researchers have found a newer machine-learning approach superior to an older one as well as to two conventional methods.

Psychology researchers have demonstrated a way to finetune diagnoses of major depression and generalized anxiety disorder by analyzing freely elaborated thoughts and feelings using machine learning and natural language processing.

Clinical nutritionists won’t be left out of the medical AI revolution, as researchers are exploring use cases for augmented diet optimization, food image recognition, risk prediction and diet pattern analysis.

Healthcare AI has potential not only for neutralizing its inherent algorithmic bias but also for personalizing its outputs to help humans address health inequities.

The system hit 88% accuracy at optimizing stimulation settings, as confirmed by brain-response patterns on neuroimaging as well as visibly observable symptom improvement in patients with Parkinson’s disease.

In a tryout trial, the technique quickly and accurately predicted shock as well as the need for early massive transfusion and major surgery.

AI is poised to help settle an argument that’s been roiling academic psychiatry for more than a century: Are bipolar disorder and schizophrenia two distinct diagnoses—or points along a single continuum?

A novel AI-based model for clinical decision support has bested established machine-learning models at predicting how patients with type-2 diabetes mellitus will respond to various categories of therapeutic drugs.

Deep neural networks are capable of tying oncological findings from genetic testing with those from medical imaging and biopsy analysis to not only validate previously discovered connections among and between the three fields but also uncover new ones.  

Researchers have developed an AI system that can differentiate primary tumors from metastatic lookalikes on routine histology slides while also helping pinpoint the sites from which the cancer sprung.

Around the web

Two different companies announced that they are recalling all lots of the medication. 

CardioSmart, an online resource for both patients and clinicians, has a new editor. 

The funding includes $8.5 billion in American Rescue Plan resources for providers who treat Medicaid, Children's Health Insurance Program and Medicare patients.

   
   
   
   
   
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