FoodNet: Recognizing Foods Using Ensemble of Deep Networks

In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food. We developed a multi-layered deep convolutional neural network (CNN) architecture that takes advantages of the features from other deep networks and improves the efficiency. Numerous classical handcrafted features and approaches are explored, among which CNNs are chosen as the best performing features. Networks are trained and fine-tuned using preprocessed images and the filter outputs are fused to achieve higher accuracy. Experimental results on the largest real-world food recognition database ETH Food-101 and newly contributed Indian food image database demonstrate the effectiveness of the proposed methodology as compared to many other benchmark deep learned CNN frameworks.Comment: 5 pages, 3 figures, 3 tables, IEEE Signal Processing Letter

Listening to the patients’ voice: a conceptual framework of the walking experience

Background walking is crucial for an active and healthy ageing, but the perspectives of individuals living with walking impairment are still poorly understood. Objectives to identify and synthesise evidence describing walking as experienced by adults living with mobility-impairing health conditions and to propose an empirical conceptual framework of walking experience. Methods we performed a systematic review and meta-ethnography of qualitative evidence, searching seven electronic databases for records that explored personal experiences of walking in individuals living with conditions of diverse aetiology. Conditions included Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture, heart failure, frailty and sarcopenia. Data were extracted, critically appraised using the NICE quality checklist and synthesised using standardised best practices. Results from 2,552 unique records, 117 were eligible. Walking experience was similar across conditions and described by seven themes: (i) becoming aware of the personal walking experience, (ii) the walking experience as a link between individuals’ activities and sense of self, (iii) the physical walking experience, (iv) the mental and emotional walking experience, (v) the social walking experience, (vi) the context of the walking experience and (vii) behavioural and attitudinal adaptations resulting from the walking experience. We propose a novel conceptual framework that visually represents the walking experience, informed by the interplay between these themes. Conclusion a multi-faceted and dynamic experience of walking was common across health conditions. Our conceptual framework of the walking experience provides a novel theoretical structure for patient-centred clinical practice, research and public health

Sex differences between women and men with COPD: A new analysis of the 3CIA study

Background: There is partial evidence that COPD is expressed differently in women than in men, namely on symptoms, pulmonary function, exacerbations, comorbidities or prognosis. There is a need to improve the characterization of COPD in females. Methods: We obtained and pooled data of 17 139 patients from 22 COPD cohorts and analysed the clinical differences by sex, establishing the relationship between these characteristics in women and the prognosis and severity of the disease. Comparisons were established with standard statistics and survival analysis, including crude and multivariate Cox-regression analysis. Results: Overall, 5355 (31.2%) women were compared with men with COPD. Women were younger, had lower pack-years, greater FEV1%, lower BMI and a greater number of exacerbations (all p < 0.05). On symptoms, women reported more dyspnea, equal cough but less expectoration (p < 0.001). There were no differences in the BODE index score in women (2.4) versus men (2.4) (p = 0.5), but the distribution of all BODE components was highly variable by sex within different thresholds of BODE. On prognosis, 5-year survival was higher in COPD females (86.9%) than in males (76.3%), p < 0.001, in all patients and within each of the specific comorbidities that we assessed. The crude and adjusted RR and 95% C.I. for death in males was 1.82 (1.69–1.96) and 1.73 (1.50–2.00), respectively. Conclusions: COPD in women has some characteristic traits expressed differently than compared to men, mainly with more dyspnea and COPD exacerbations and less phlegm, among others, although long-term survival appears better in female COPD patients

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice

Mortality prediction in chronic obstructive pulmonary disease comparing the GOLD 2015 and GOLD 2019 staging: a pooled analysis of individual patient data

In 2019, The Global Initiative for Chronic Obstructive Lung Disease (GOLD) modified the grading system for patients with COPD, creating 16 subgroups (1A-4D). As part of the COPD Cohorts Collaborative International Assessment (3CIA) initiative, we aim to compare the mortality prediction of the 2015 and 2019 COPD GOLD staging systems. We studied 17 139 COPD patients from the 3CIA study, selecting those with complete data. Patients were classified by the 2015 and 2019 GOLD ABCD systems, and we compared the predictive ability for 5-year mortality of both classifications. In total, 17139 patients with COPD were enrolled in 22 cohorts from 11 countries between 2003 and 2017; 8823 of them had complete data and were analysed. Mean +/- SD age was 63.9 +/- 9.8 years and 62.9% were male. GOLD 2019 classified the patients in milder degrees of COPD. For both classifications, group D had higher mortality. 5-year mortality did not differ between groups B and C in GOLD 2015; in GOLD 2019, mortality was greater for group B than C. Patients classified as group A and B had better sensitivity and positive predictive value with the GOLD 2019 classification than GOLD 2015. GOLD 2015 had better sensitivity for group C and D than GOLD 2019. The area under the curve values for 5-year mortality were only 0.67 (95% CI 0.66-0.68) for GOLD 2015 and 0.65 (95% CI 0.63-0.66) for GOLD 2019. The new GOLD 2019 classification does not predict mortality better than the previous GOLD 2015 system