Methods: Histopathological examination of appendicectomies conducted between 2016 and 2017 in Melaka Hospital, Malaysia were traced and categorised into three groups: i) G1 (normal appendix), ii) G2 (acute appendicitis) and iii) G3 (perforated appendicitis). The reports were randomised and a total of 338 samples were collected. NLR values were compared between the three different groups and analysed.
Results: The median values of NLR for G1, G2 and G3 were 2.37, 5.25 and 9.27, respectively. We found a statistically significant difference in NLR between G1 and G2 (P < 0.001), and G2 and G3 (P < 0.001). The diagnostic values of NLR for acute appendicitis and perforated appendicitis were 3.11 (sensitivity: 75.23%, specificity: 68.70%) and 6.17 (sensitivity: 76.32%, specificity: 58.72%), respectively. There was a substantial correlation between NLR and disease severity, and a moderate correlation between NLR and duration of admission.
Conclusion: NLR, with a sensitivity of 75.23% and specificity of 68.70%, is a useful and reliable adjunct in diagnosing acute appendicitis. Hence, it will help in reducing the rate of negative appendicectomies.
OBJECTIVE: This study aimed to review and analyse literature related to the detection and classification of acute leukaemia. The factors that were considered to improve understanding on the field's various contextual aspects in published studies and characteristics were motivation, open challenges that confronted researchers and recommendations presented to researchers to enhance this vital research area.
METHODS: We systematically searched all articles about the classification and detection of acute leukaemia, as well as their evaluation and benchmarking, in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 2007 to 2017. These indices were considered to be sufficiently extensive to encompass our field of literature.
RESULTS: Based on our inclusion and exclusion criteria, 89 articles were selected. Most studies (58/89) focused on the methods or algorithms of acute leukaemia classification, a number of papers (22/89) covered the developed systems for the detection or diagnosis of acute leukaemia and few papers (5/89) presented evaluation and comparative studies. The smallest portion (4/89) of articles comprised reviews and surveys.
DISCUSSION: Acute leukaemia diagnosis, which is a field requiring automated solutions, tools and methods, entails the ability to facilitate early detection or even prediction. Many studies have been performed on the automatic detection and classification of acute leukaemia and their subtypes to promote accurate diagnosis.
CONCLUSIONS: Research areas on medical-image classification vary, but they are all equally vital. We expect this systematic review to help emphasise current research opportunities and thus extend and create additional research fields.