MATERIALS AND METHODS: A DCN model was developed using pill images captured with mobile phones under unconstraint environments. The performance of the DCN model was compared to two baseline methods of hand-crafted features.
RESULTS: The DCN model outperforms the baseline methods. The mean accuracy rate of DCN at Top-1 return was 95.35%, whereas the mean accuracy rates of the two baseline methods were 89.00% and 70.65%, respectively. The mean accuracy rates of DCN for Top-5 and Top-10 returns, i.e., 98.75% and 99.55%, were also consistently higher than those of the baseline methods.
DISCUSSION: The images used in this study were captured at various angles and under different level of illumination. DCN model achieved high accuracy despite the suboptimal image quality.
CONCLUSION: The superior performance of DCN underscores the potential of Deep Learning model in the application of pill identification and verification.
METHODS: Three databases were searched to identify randomized clinical trials (RCTs) published up until September 2017. Retrieved RCTs were evaluated using the revised Cochrane Risk of Bias Tool. The primary efficacy outcome of interest was the success rate of IANB anesthesia. Meta-analytic estimates (risk ratio [RR] with 95% confidence intervals [CIs]) performed using a random effects model and publication bias determined using funnel plot analysis were assessed. Random errors were evaluated with trial sequential analyses, and the quality of evidence was appraised using a Grading of Recommendations, Assessment, Development and Evaluation approach.
RESULTS: Thirteen RCTs (N = 1034) were included. Eight studies had low risk of bias. Statistical analysis of good-quality RCTs showed a significant beneficial effect of any NSAID in increasing the anesthetic success of IANBs compared with placebo (RR = 1.92; 95% CI, 1.55-2.38). Subgroup analyses showed a similar beneficial effect for ibuprofen, diclofenac, and ketorolac (RR = 1.83 [95% CI, 1.43-2.35], RR = 2.56 [95% CI, 1.46-4.50], and RR = 2.07 [95% CI, 1.47-2.90], respectively). Dose-dependent ibuprofen >400 mg/d (RR = 1.85; 95% CI, 1.39-2.45) was shown to be effective; however, ibuprofen ≤400 mg/d showed no association (RR = 1.78; 95% CI, 0.90-3.55). TSA confirmed conclusive evidence for a beneficial effect of NSAIDs for IANB premedication. The Grading of Recommendations, Assessment, Development and Evaluation approach did not reveal any concerns regarding the quality of the results.
CONCLUSIONS: Oral premedication with NSAIDs and ibuprofen (>400 mg/d) increased the anesthetic success of IANBs in patients with irreversible pulpitis.
METHODS: Application of nanotechnology in medicine have perceived a great evolution during past few decades. Nanoemulsion, submicron sized thermodynamically stable distribution of two immiscible liquids, has gained extensive importance as a nanocarrier to improve chemotherapies seeking to overcome the limitations of drug solubilization, improving systemic delivery of the chemotherapeutics to the site of action to achieve a promising inhibitory in tumor growth profile with reduced systemic toxicity.
RESULTS AND CONCLUSION: This review has focused on potential application of nanoemulsion in the translational research and its role in chemotherapy using oral, parenteral and transdermal route to enhance systemic availability of poorly soluble drug. In summary, nanoemulsion is a multifunctional nanocarrier capable of enhancing drug delivery potential of cytotoxic agents, thereby, can improve the outcomes of cancer treatment by increasing the life-span of the patient and quality of life, however, further clinical research and characterization of interactive reactions should need to be explored.