We conducted a systematic review and meta-analysis of the diagnostic performance of current deep learning algorithms for the diagnosis of lung cancer. We searched major databases up to June 2022 to include studies that used artificial intelligence to diagnose lung cancer, using the histopathological analysis of true positive cases as a reference. The quality of the included studies was assessed independently by two authors based on the revised Quality Assessment of Diagnostic Accuracy Studies. Six studies were included in the analysis. The pooled sensitivity and specificity were 0.93 (95% CI 0.85–0.98) and 0.68 (95% CI 0.49–0.84), respectively. Despite the significantly high heterogeneity for sensitivity (I² = 94%, p < 0.01) and specificity (I² = 99%, p < 0.01), most of it was attributed to the threshold effect. The pooled SROC curve with a bivariate approach yielded an area under the curve (AUC) of 0.90 (95% CI 0.86 to 0.92). The DOR for the studies was 26.7 (95% CI 19.7–36.2) and heterogeneity was 3% (p = 0.40). In this systematic review and meta-analysis, we found that when using the summary point from the SROC, the pooled sensitivity and specificity of DL algorithms for the diagnosis of lung cancer were 93% and 68%, respectively.

Objective: To evaluate the association between shear wave elastography parameters and arterial resistance in kidney transplant recipients. Materials and Methods: This was a prospective cross-sectional study involving consecutive adult kidney transplant recipients. All patients underwent color Doppler to evaluate the resistive index (RI) and ultrasound shear wave elastography for the quantification of renal allograft stiffness. Results: We evaluated 55 patients, of whom 9 (16.4%) had an RI defined as abnormal (≥ 0.79) and 46 (83.6%) had an RI defined as normal (< 0.79). The mean age was higher in the abnormal RI group than in the normal RI group (68.0 ± 8.6 years vs. 42.6 ± 14.1 years; p < 0.001), as was the mean shear wave velocity (2.6 ± 0.4 m/s vs. 2.2 ± 0.4 m/s; p = 0.013). Multivariate analysis identified two independent predictors of arterial resistance: age (OR = 1.169; 95% CI: 1.056 to 1.294; p = 0.003) and shear wave velocity (OR = 17.1; 95% CI: 1.137 to 257.83; p = 0.040). Conclusion: We observed an association between rigidity in the cortex of the transplanted kidney, as evaluated by shear wave elastography, and arterial resistance, as evaluated by color Doppler, in kidney transplant recipients.

Objective: To systematically review and meta-analyze bulk RNA sequencing studies comparing Alzheimer’s disease (AD) patients with controls in human brain tissue, assessing study quality and identifying key genes and pathways. Methods: We searched PubMed, Web of Science, and Scopus on September 23, 2023, for studies using bulk RNAseq on primary human brain tissue from AD patients and controls. Excluded were non-primary tissue, re-analyses without new data, limited RNA types and gene panels. Quality was assessed with a 10-category tool. Meta-analysis used high-quality datasets. Results: From 3,266 records, 24 studies met criteria. Meta-analysis found 571 differentially expressed genes (DEGs) in temporal lobe and 189 in frontal lobe; overlapping pathways included "Tube morphogenesis" and "Neuroactive ligand-receptor interaction." Limitations: Study heterogeneity and limited data tables constrained the review. Conclusions: Rigorous methods are vital in AD transcriptomic studies. Findings enhance understanding of transcriptomic changes, aiding biomarker and therapeutic development. Registration: PROSPERO (CRD42023466522).