Web System Prototype based on speech recognition to construct medical reports in Brazilian Portuguese.

The overall purpose of automatic speech recognition systems is to make possible the interaction between humans and electronic devices through speech. For example, the content captured from user's speech using a microphone can be transcribed into text. In general, such systems should be able to overcome adversities such as noise, communication channel variability, speaker's age and accent, speech speed, concurrent speeches from other speakers and spontaneous speech. Despite this challenging scenario, this study aims to develop a Web System Prototype to generate medical reports through automatic speech recognition in the Brazilian Portuguese language. The prototype was developed by applying a Software Engineering technique named Delivery in Stage. During the conduction of this technique, we integrated the Google Web Speech API and Microsoft Bing Speech API into the prototype to increase the number of compatible platforms. These automatic speech recognition systems were individually evaluated in the task of transcribing the dictation of a medical area text by 30 volunteers. The recognition performance was evaluated according to the Word Error Rate measure. The Google system achieved an error rate of 12.30%, which was statistically significantly better (p-value <0.0001) than the Microsoft one: 17.68%. Conducting this work allowed us to conclude that these automatic speech recognition systems are compatible with the prototype and can be used in the medical field. The findings also suggest that, besides supporting medical reports construction, the Web System Prototype can be useful for purposes such as recording physicians' notes during a clinical procedure.

Plasma Lipidomic Signature of Rectal Adenocarcinoma Reveals Potential Biomarkers.

BACKGROUND: Rectal adenocarcinoma (RAC) is a common malignant tumor of the digestive tract and survival is highly dependent upon stage of disease at diagnosis. Lipidomic strategy can be used to identify potential biomarkers for establishing early diagnosis or therapeutic programs for RAC. OBJECTIVE: To evaluate the lipoperoxidation biomarkers and lipidomic signature in the plasma of patients with RAC (n = 23) and healthy controls (n = 18). METHODS: Lipoperoxidation was evaluated based on malondialdehyde (MDA) and F2-isoprostane levels and the lipidomic profile obtained by gas chromatography and high resolution mass spectrometry (ESI-q-TOF) associated with a multivariate statistical technique. RESULTS: The most abundant ions identified in the RAC patients were those of protonated phosphatidylcholine and phosphatidylethanolamine. It was found that a lisophosphatidylcholine (LPC) plasmalogen containing palmitoleic acid [LPC (P-16:1)], with highest variable importance projection score, showed a tendency to be lower in the cancer patients. A reduction of n - 3 polyunsaturated fatty acids was observed in the plasma of these patients. MDA levels were higher in patients with advanced cancer (stages III/IV) than in the early stages groups and the healthy group (p < 0.05). No differences in F2-isoprostane levels were observed among these groups. CONCLUSION: This study shows that the reduction in plasma levels of LPC plasmalogens associated with an increase in MDA levels may indicate increased oxidative stress in these patients and identify the metabolite LPC (P-16:1) as a putatively novel lipid signature for RAC.