Smart Multi-Model Emotion Recognition System with Deep learning

Emotion recognition is added a new dimension to the sentiment analysis. This paper presents a multi-modal human emotion recognition web application by considering of three traits includes speech, text, facial expressions, to extract and analyze emotions of people who are giving interviews. Now a days there is a rapid development of Machine Learning, Artificial Intelligence and deep learning, this emotion recognition is getting more attention from researchers. These machines are said to be intelligent only if they are able to do human recognition or sentiment analysis. Emotion recognition helps in spam call detection, blackmailing calls, customer services, lie detectors, audience engagement, suspicious behavior. In this paper focus on facial expression analysis is carried out by using deep learning approaches with speech signals and input text

A Prospective Cohort Study on Diabetic Foot Infections with Emphasis on Identifiable Risk Factors in Patients Attending Tertiary Care Centre

Background: Foot infections are one of the most commonly observed complications in diabetic patients and are associated with high morbidity and risk of lower extremity amputation. Foot infections account for about 20% of all hospitalizations in people with diabetes and at least 50% of all non-traumatic lower-limb amputations performed annually. Objective: To identify the risk factors in patients with diabetic foot infections attending tertiary care centre. Method: It is a longitudinal prospective study in which patients attending the tertiary care centre with diabetic foot infections meeting the inclusion criteria were enrolled after obtaining the informed consent form. Results and discussion: The results of this study revealed that the overall prevalence of DFI was seen more in males (61.42%) when compared to females (38.57%). The results also showed that the risk of DFI was more with trauma(44.28%) followed by the long duration of DM (28.57%) > wound (15.71%) > uncontrolled DM & prior foot ulcer (5.7%) which indicates a lack of awareness, longer duration of  DM, poor glycemic control were the main risk factors causing diabetic foot problems. Conclusion: The results suggest that lack of awareness, poor glycemic control, and long duration of diabetes were the main risk factors causing DFI. Therefore, efforts to prevent infections should be targeted at people with traumatic foot wounds especially those that are chronic and recurrent. Foot care education would be the foremost important way of dealing with this serious problem. Keywords: Morbidity, lower-extremity amputation, trauma, glycemic control