Smart food waste management : embedded machine learning vs cloud based solutions

In Switzerland, 2.8 million tons of food are lost or wasted across all stages of food production - every year. This equates to approximately 330 kg of food waste per person. By analysing and classifying discarded food with a smart waste analysis system combined with machine learning, valuable insights can be gained and the amount of wasted food can be significantly reduced. In this paper, we present how we have developed an embedded system which helps to solve this task. The embedded system operates in a decentralized manner: It captures an image every time food is thrown into a bin. The discarded food is identified and classified with machine learning algorithms. This provides a detailed insight into the structure of food waste for customers, e.g. restaurants or canteens. We implemented the machine learning algorithm directly on the embedded systems control unit. We found that running machine learning directly on embedded devices has many advantages compared to running them in the cloud: We saved significant amounts of cloud storage and reduced power consumption by up to a factor 100. In addition, privacy was increased and required bandwidth reduced because only the machine learning results are forwarded to the cloud, not the full data

Comparative Study of Acute Kidney Injury in Liver Transplantation: Donation after Circulatory Death versus Brain Death

BACKGROUND Acute kidney injury (AKI) after orthotopic liver transplantation (OLT) contributes to morbidity and mortality. Donation after circulatory death (DCD) has been established to increase the pool of organs. While surgical complications are reported to be comparable in DCD and donation after brain death (DBD) OLT, there is a knowledge gap concerning adverse kidney events in these 2 groups. MATERIAL AND METHODS In this retrospective cohort study, 154 patients received a DBD and 68 received a DCD organ (2016-2020). The primary outcome was a major adverse kidney event within 30 days (MAKE-30). The secondary outcome was dynamics of AKI and kidney replacement therapy (KRT) during the first postoperative week and on postoperative day 30. Incidence and resolution from AKI and KRT and patient survival (PS) 30 days after OLT were compared between the DCD and DBD recipients. RESULTS MAKE-30 incidence after OLT was comparable in DCD (n=27, 40%) vs DBD (n=41, 27%) recipients (risk ratio 1.49 [95% CI 1.01, 2.21], p=0.073). AKI incidence was comparable in DCD (n=58, 94%) vs DBD (n=95, 82%) recipients (risk ratio 1.14 [95% CI: 1.03, 1.27], P=0.057). Overall, 40% (n=88) of patients required KRT, with no difference between DCD (n=27, 40%) vs DBD (n=61, 40%) recipients (risk ratio 1.00 [95% CI 0.71, 1.43], P>0.999). Resolution of AKI by day 30 was lower in DCD (n=29, 50%) than in DBD (n=66, 69%) recipients (risk ratio 0.71 [95% CI: 0.53, 0.95], P=0.032). Survival after 30 days (DCD: n=64, 94% vs DBD: n=146, 95%, risk ratio 0.99 [95% CI 0.93, 1.06], P>0.999) was also comparable. CONCLUSIONS MAKE-30, short-term renal outcome, and survival did not significantly differ between DBD and DCD-OLT. Resolution of AKI by day 30 was lower in DCD than in DBD recipients

MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets

PURPOSE To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest CT datasets. The feasibility is demonstrated for 2D coronal ultrafast balanced SSFP (ufSSFP) MRI. METHODS Lung lobes of 250 publicly accessible CT datasets of adults were segmented with an open-source CT-specific algorithm. To match 2D ufSSFP MRI data of pediatric patients, both CT data and segmentations were translated into pseudo-MR images that were masked to suppress anatomy outside the lung. Network-1 was trained with pseudo-MR images and lobe segmentations and then applied to 1000 masked ufSSFP images to predict lobe segmentations. These outputs were directly used as targets to train Network-2 and Network-3 with non-masked ufSSFP data as inputs, as well as an additional whole-lung mask as input for Network-2. Network predictions were compared to reference manual lobe segmentations of ufSSFP data in 20 pediatric cystic fibrosis patients. Manual lobe segmentations were performed by splitting available whole-lung segmentations into lobes. RESULTS Network-1 was able to segment the lobes of ufSSFP images, and Network-2 and Network-3 further increased segmentation accuracy and robustness. The average all-lobe Dice similarity coefficients were 95.0 ± 2.8 (mean ± pooled SD [%]) and 96.4 ± 2.5, 93.0 ± 2.0; and the average median Hausdorff distances were 6.1 ± 0.9 (mean ± SD [mm]), 5.3 ± 1.1, 7.1 ± 1.3 for Network-1, Network-2, and Network-3, respectively. CONCLUSION Recurrent neural network lung lobe segmentation of 2D ufSSFP imaging is feasible, in good agreement with manual segmentations. The proposed workflow might provide access to automated lobe segmentations for various lung MRI examinations and quantitative analyses

MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets.

PURPOSE To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest CT datasets. The feasibility is demonstrated for 2D coronal ultrafast balanced SSFP (ufSSFP) MRI. METHODS Lung lobes of 250 publicly accessible CT datasets of adults were segmented with an open-source CT-specific algorithm. To match 2D ufSSFP MRI data of pediatric patients, both CT data and segmentations were translated into pseudo-MR images that were masked to suppress anatomy outside the lung. Network-1 was trained with pseudo-MR images and lobe segmentations and then applied to 1000 masked ufSSFP images to predict lobe segmentations. These outputs were directly used as targets to train Network-2 and Network-3 with non-masked ufSSFP data as inputs, as well as an additional whole-lung mask as input for Network-2. Network predictions were compared to reference manual lobe segmentations of ufSSFP data in 20 pediatric cystic fibrosis patients. Manual lobe segmentations were performed by splitting available whole-lung segmentations into lobes. RESULTS Network-1 was able to segment the lobes of ufSSFP images, and Network-2 and Network-3 further increased segmentation accuracy and robustness. The average all-lobe Dice similarity coefficients were 95.0 ± 2.8 (mean ± pooled SD [%]) and 96.4 ± 2.5, 93.0 ± 2.0; and the average median Hausdorff distances were 6.1 ± 0.9 (mean ± SD [mm]), 5.3 ± 1.1, 7.1 ± 1.3 for Network-1, Network-2, and Network-3, respectively. CONCLUSION Recurrent neural network lung lobe segmentation of 2D ufSSFP imaging is feasible, in good agreement with manual segmentations. The proposed workflow might provide access to automated lobe segmentations for various lung MRI examinations and quantitative analyses

A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications

​© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.When applying deep learning methods in an industrial vision application, they often fall short of the performance shown in a clean and controlled lab environment due to data quality issues. Few would consider the actual labels as a driving factor, yet inaccurate label data can impair model performance significantly. However, being able to mitigate inaccurate or incomplete labels might also be a cost-saver for real-world projects. Here, we survey state-of-the-art deep learning approaches to resolve such missing labels, noisy labels, and partially labeled data in the prospect of an industrial vision application. We systematically present un-, weakly, and semi-supervised approaches from ’A’ like anomaly detection to ’Z’ like zero-shot classification to resolve these challenges by embracing them

Donor-derived fulminant herpes simplex virus hepatitis after liver transplantation: Two cases and review of literature

BACKGROUND Fulminant herpetic hepatitis due to herpes simplex virus (HSV), serotype 1 or 2, is a rare but often fatal complication after solid organ transplantation (SOT). HSV hepatitis in SOT recipients can occur either due to primary infection acquired post transplantation, viral reactivation in a seropositive patient, or as donor-derived infection. Cases of fatal hepatitis have been reported in the liver as well as in other SOT recipients. The fatal outcome is mostly due to delayed diagnosis and treatment, which is explained by the lack of clinical specificity of HSV hepatitis. METHODS We report two cases of fatal donor-derived HSV hepatitis in liver-transplanted recipients. We reviewed all published cases of donor-derived HSV infections after SOT with an evaluation of the presence of prophylaxis and outcome. RESULTS In both liver recipients, the retrospective determination of HSV serostatus was negative, and both cases occurred in the absence of cytomegalovirus or HSV prophylaxis. A review of the literature showed a significant series of cases of severe hepatitis, mostly fatal, as well as the absence of specific preventive therapy guidelines in cases of HSV serology mismatch. CONCLUSIONS The occurrence of two fatal donor-derived hepatitis made the Swiss Transplant Infectious Diseases working group modify its national recommendations regarding pretransplant serostatus determination and HSV prophylaxis after liver transplantation. Further studies are needed to assess this approach

The impact of segmentation on whole-lung functional MRI quantification: Repeatability and reproducibility from multiple human observers and an artificial neural network.

PURPOSE To investigate the repeatability and reproducibility of lung segmentation and their impact on the quantitative outcomes from functional pulmonary MRI. Additionally, to validate an artificial neural network (ANN) to accelerate whole-lung quantification. METHOD Ten healthy children and 25 children with cystic fibrosis underwent matrix pencil decomposition MRI (MP-MRI). Impaired relative fractional ventilation (RFV ) and relative perfusion (RQ ) from MP-MRI were compared using whole-lung segmentation performed by a physician at two time-points (At1 and At2 ), by an MRI technician (B), and by an ANN (C). Repeatability and reproducibility were assess with Dice similarity coefficient (DSC), paired t-test and Intraclass-correlation coefficient (ICC). RESULTS The repeatability within an observer (At1 vs At2 ) resulted in a DSC of 0.94 ± 0.01 (mean ± SD) and an unsystematic difference of -0.01% for RFV (P = .92) and +0.1% for RQ (P = .21). The reproducibility between human observers (At1 vs B) resulted in a DSC of 0.88 ± 0.02, and a systematic absolute difference of -0.81% (P 0.98 for all variables and comparisons. CONCLUSIONS Despite high overall agreement, there were systematic differences in lung segmentation between observers. This needs to be considered for longitudinal studies and could be overcome by using an ANN, which performs as good as human observers and fully automatizes MP-MRI post-processing

Long-term ketamine infusion-induced cholestatic liver injury in COVID-19-associated acute respiratory distress syndrome

Background: A higher-than-usual resistance to standard sedation regimens in COVID-19 patients suffering from acute respiratory distress syndrome (ARDS) has led to the frequent use of the second-line anaesthetic agent ketamine. Simultaneously, an increased incidence of cholangiopathies in mechanically ventilated patients receiving prolonged infusion of high-dose ketamine has been noted. Therefore, the objective of this study was to investigate a potential dose–response relationship between ketamine and bilirubin levels. Methods: Post hoc analysis of a prospective observational cohort of patients suffering from COVID-19-associated ARDS between March 2020 and August 2021. A time-varying, multivariable adjusted, cumulative weighted exposure mixed-effects model was employed to analyse the exposure–effect relationship between ketamine infusion and total bilirubin levels. Results: Two-hundred forty-three critically ill patients were included into the analysis. Ketamine was infused to 170 (70%) patients at a rate of 1.4 [0.9–2.0] mg/kg/h for 9 [4–18] days. The mixed-effects model revealed a positively correlated infusion duration–effect as well as dose–effect relationship between ketamine infusion and rising bilirubin levels (p < 0.0001). In comparison, long-term infusion of propofol and sufentanil, even at high doses, was not associated with increasing bilirubin levels (p = 0.421, p = 0.258). Patients having received ketamine infusion had a multivariable adjusted competing risk hazard of developing a cholestatic liver injury during their ICU stay of 3.2 [95% confidence interval, 1.3–7.8] (p = 0.01). Conclusions: A causally plausible, dose–effect relationship between long-term infusion of ketamine and rising total bilirubin levels, as well as an augmented, ketamine-associated, hazard of cholestatic liver injury in critically ill COVID-19 patients could be shown. High-dose ketamine should be refrained from whenever possible for the long-term analgosedation of mechanically ventilated COVID-19 patients

The Angiopoietin-2/Angiopoietin-1 ratio increases early in burn patients and predicts mortality

Background: Angiopoietin-2 (Angpt-2) is involved in the pathogenesis of the capillary leak syndrome in sepsis and has been shown to be associated with worse outcomes in diverse critical illnesses. It is however unclear whether Angpt-2 plays a similar role in severely burned patients during the early phase characterized by massive capillary leakage. Our aim was to analyze the Angiopoietin-2/Angiopoietin-1 ratio (Angpt-2/Angpt-1 ratio) over the first two days in critically ill burn patients and examine its association with survival and further clinical parameters. Methods: Adult burn patients with a total burn surface area (TBSA) ≥ 20% treated in the burn intensive care unit (ICU) of the University Hospital of Zurich, Switzerland, were included. Serum samples were collected prospectively and serum Angpt-1 and Angpt-2 were measured by enzyme-linked immunosorbent assay (ELISA) over the first two days after burn insult and stratified according to survival status, TBSA and the abbreviated burn severity index (ABSI). Due to hemodilution in the initial resuscitation phase, the Angpt-2/Angpt-1 ratio was normalized to albumin. Results: Fifty-six patients were included with a median age of 51.5 years. Overall mortality was 14.3% (8/56 patients). The total amount of infused crystalloids was 12́902 ml (IQR 9́362-16́770 ml) at 24 h and 18́461 ml (IQR 13́024-23́766 ml) at 48 h. The amount of substituted albumin was 20 g (IQR 10-50 g) at 24 h and 50 g (IQR 20-60 g) at 48 h. The albumin-corrected Angpt-2/Angpt-1 ratios increased over the first 48 h after the burn insult (d0: 0.5 pg*l/ml*g [IQR 0.24 - 0.80 pg*l/ml*g]; d1: 0.83 pg*l/ml*g [IQR 0.29 - 1.98 pg*l/ml*g]; d2: 1.76 pg*l/ml*g [IQR 0.70 - 3.23 pg*l/ml*g]; p < 0.001) and were significantly higher in eventual ICU non-survivors (p = 0.005), in patients with a higher TBSA (p = 0.001) and in patients with a higher ABSI (p = 0.001). Conclusions: In analogy to the pathological host response in sepsis, the Angpt-2/Angpt-1 ratio steadily increases in the first two days in critically ill burn patients, suggesting a putative involvement in the pathogenesis of capillary leakage in burns. A higher Angpt-2/Angpt-1 ratio is associated with mortality, total burn surface area and burn scores. Keywords: Angiopoietin-2/Angiopoietin-1 ratio; Burn patients; Capillary leak; Critically ill; Total burn surface area

Donor-derived fulminant herpes simplex virus hepatitis after liver transplantation : Two cases and review of literature

Background: Fulminant herpetic hepatitis due to herpes simplex virus (HSV), serotype 1 or 2, is a rare but often fatal complication after solid organ transplantation (SOT). HSV hepatitis in SOT recipients can occur either due to primary infection acquired post transplantation, viral reactivation in a seropositive patient, or as donor-derived infection. Cases of fatal hepatitis have been reported in the liver as well as in other SOT recipients. The fatal outcome is mostly due to delayed diagnosis and treatment, which is explained by the lack of clinical specificity of HSV hepatitis. Methods: We report two cases of fatal donor-derived HSV hepatitis in liver-transplanted recipients. We reviewed all published cases of donor-derived HSV infections after SOT with an evaluation of the presence of prophylaxis and outcome. Results: In both liver recipients, the retrospective determination of HSV serostatus was negative, and both cases occurred in the absence of cytomegalovirus or HSV prophylaxis. A review of the literature showed a significant series of cases of severe hepatitis, mostly fatal, as well as the absence of specific preventive therapy guidelines in cases of HSV serology mismatch. Conclusions: The occurrence of two fatal donor-derived hepatitis made the Swiss Transplant Infectious Diseases working group modify its national recommendations regarding pretransplant serostatus determination and HSV prophylaxis after liver transplantation. Further studies are needed to assess this approach.</p