Can Domain Adaptation Improve Accuracy and Fairness of Skin Lesion Classification?

Deep learning-based diagnostic system has demonstrated potential in classifying skin cancer conditions when labeled training example are abundant. However, skin lesion analysis often suffers from a scarcity of labeled data, hindering the development of an accurate and reliable diagnostic system. In this work, we leverage multiple skin lesion datasets and investigate the feasibility of various unsupervised domain adaptation (UDA) methods in binary and multi-class skin lesion classification. In particular, we assess three UDA training schemes: single-, combined-, and multi-source. Our experiment results show that UDA is effective in binary classification, with further improvement being observed when imbalance is mitigated. In multi-class task, its performance is less prominent, and imbalance problem again needs to be addressed to achieve above-baseline accuracy. Through our quantitative analysis, we find that the test error of multi-class tasks is strongly correlated with label shift, and feature-level UDA methods have limitations when handling imbalanced datasets. Finally, our study reveals that UDA can effectively reduce bias against minority groups and promote fairness, even without the explicit use of fairness-focused techniques

Spatial distribution of dynamics characteristic in the intermittent aeration static composting of sewage sludge

Spatial differences and temporal changes in biological activity characteristics were investigated in a static reactor using intermittent aeration during the sewage sludge composting process. Pumice was proposed as a bulking agent in the composting of sewage sludge. Variations in temperature, moisture, oxygen level, volatile solids, specific oxygen uptake rate (SOUR) and dehydrogenase activity (DHA) were determined during 28. days of composting. The peak temperature in the upper region of the reactor was 10 °C higher than that at the bottom. The moisture level in the middle region was significantly higher than that of other positions. Analysis of SOUR and DHA indicated that the lowest level of sludge stability was at the bottom region. These spatial and temporal differences in biochemical dynamics in the static system could extend the composting period and affect product uniformity

Association of dyslipidemia with renal cell carcinoma: a 1∶2 matched case-control study.

Abnormal serum lipid profiles are associated with the risk of some cancers, but the direction and magnitude of the association with renal cell carcinoma is unclear. We explore the relationship between serum lipids and renal cell carcinoma via a matched case-control study. A 1∶2-matched case-control study design was applied, where one renal cell carcinoma patient was matched to two non-renal-cell-carcinoma residents with respect to age (±0 year) and gender. Cases (n = 248) were inpatients with a primary diagnosis of renal cell carcinoma, confirmed by pathology after operations. Controls were sampled from a community survey database matched on age and gender with cases, 2 controls for each case. Stratified Cox proportional hazard regression analysis was used to obtain hazard ratios and corresponding 95% confidence intervals of lipids level and dyslipidemia for the risk of renal cell carcinoma. Elevated serum cholesterol (p<0.001), LDL cholesterol (p<0.001), and HDL cholesterol (p = 0.003) are associated with decreased hazard of renal cell carcinoma, adjusting for obesity, smoke, hypertension and diabetes. However, risk caused by hTG showed no statistical significance (p = 0.263). This study indicates that abnormal lipid profile influences the risk of renal cell carcinoma

Description of the renal cell carcinoma.

<p>Description of the renal cell carcinoma.</p

Safety of Autologous Cord Blood Cells for Preterms: A Descriptive Study

Background. Preterm birth complications are one of the leading causes of death among children under 5 years of age. Despite advances in medical care, many survivors face a lifetime of disability, including mental and physical retardation, and chronic lung disease. More recently, both allogenic and autogenic cord blood cells have been applied in the treatment of neonatal conditions such as hypoxic-ischemic encephalopathy (HIE) and bronchopulmonary dysplasia (BPD). Objective. To assess the safety of autologous, volume- and red blood cell- (RBC-) reduced, noncryopreserved umbilical cord blood (UCB) cell infusion to preterm infants. Method. This study was a phase I, open-label, single-arm, single-center trial to evaluate the safety of autologous, volume- and RBC-reduced, noncryopreserved UCB cell (5 × 107cells/kg) infusion for preterm infants <37 weeks gestational age. UCB cell characteristics, pre- and postinfusion vital signs, and laboratory investigations were recorded. Clinical data including mortality rates and preterm complications were recorded. Results. After processing, (22.67 ± 4.05) ml UCB cells in volume, (2.67 ± 2.00) × 108 cells in number, with (22.67 ± 4.05) × 106 CD34+, (3.72 ± 3.25) × 105 colony forming cells (CFU-GM), and (99.7 ± 0.17%) vitality were infused to 15 preterm infants within 8 hours after birth. No adverse effects were noticed during treatment. All fifteen patients who received UCB infusion survived. The duration of hospitalization ranged from 4 to 65 (30 ± 23.6) days. Regarding preterm complications, no BPD, necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP) was observed. There were 1/15 (7%) infant with intraventricular hemorrhage (IVH), 5/15 (33.3%) infants with ventilation-associated pneumonia, and 10/15 (66.67%) with anemia, respectively. Conclusions. Collection, preparation, and infusion of fresh autologous UCB cells to preterm infants is feasible and safe. Adequately powered randomized controlled studies are needed

Description and comparison of clinical and biochemical characteristics of the study subjects^*.

*<p>Quantitative data were presented as mean±SD, and categorical data as N (percentage);</p>†<p>P-values were obtained from univariate Cox regression.</p

Hazard ratios of plasma lipids and dyslipidemia from stratified Cox regression models.

<p>Multifactor adjustment was for obesity, smoke, hypertension, and diabetes. Black squares represent the hazard ratios, and error bars indicate the 95% confidence intervals (CIs).</p