Machine Learning based Postpartum Hemorrhage Prediction Model
Postpartum hemorrhage (PPH) is an obstetric emergency instigated by excessive blood loss which occurs frequently after the delivery. The PPH can result in volume depletion, hypovolemic shock, and anemia.
AI enabled Prototype to identify the patient-specific treatments to preserve vision for persons with diabetes.
The uncertainty of sight loss from diabetic retinopathy has dropped dramatically over the past few decades with advancements in medications like laser surgery, intraocular drug delivery, diabetes and blood pressure medications. But, diabetes remains to be a vital cause of blindness. This proposal compiles a novel idea in diabetic retinopathy analysis and contributes a prospect on possibilities for future studies. The new findings of the pathophysiology of diabetes and diabetic retinopathy provide a prominent control in metabolism.The more outcomes can be predicted using Structure-function analyses and intraocular drug therapy. The core objective of this proposal to develop a prototype to detect and quantify vision loss and also to provide patient-specific treatments in a better way using Artificial Intelligence Techniques. Through this, it is possible to conserve eyesight for diabetes persons and as well as to diagnose the patients upon their needs.
Early Detection of Parkinson’s through Handwriting Analysis
Here are about 11 million Parkinson’s and Essential Tremor patients in the china , with approximately 200,000 to 3 million additional people per year being affected by this disease. Our work supports a larger research initiative to help this population. Although various treatments/therapies exist to help improve tremor conditions, it would be valuable if we could detect these conditions in the earlier stages of their development. Our team has discovered that this early detection can be achieved through handwriting analysis. The promise here is that patients’ handwriting can be analyzed so that the initiation and progression of the disease, as well as interventions on the disease can be quantitatively tracked. The purpose of our work is to identify if our method of analysis is a reliable resource for observing patients’ handwriting.
Facial expressions recognition and discrimination in Parkinson’s disease
Emotion processing impairment is a common non-motor symptom in Parkinson’s Disease (PD). Previous literature reported conflflicting results concerning, in particular, the performance for different emotions, the relation with cognitive and neuropsychiatric symptoms and the affected stage of processing. This study aims at assessing emotion recognition and discrimination in PD. Recognition of six facial expressions was studied in order to clarify its relationship with motor, cognitive and neuropsychiatric symptoms. Sensitivity in discriminating happy and fearful faces was investigated to address controversial fifindings on impairment in early stages of emotion processing.