Automated detection of actinic keratoses in clinical photographs

Backgroun

Effects of nutrition intervention strategies in the primary prevention of overweight and obesity in school settings: a protocol for a systematic review and network meta-analysis

Background!#!Overweight and obesity in children and adolescents are major public health challenges affecting quality of life and representing important risk factors in the development of non-communicable diseases. School environments provide great possibilities for the primary prevention of overweight and obesity and different school-based nutrition interventions are available. However, existing research on school-based nutrition interventions has important limitations and no network meta-analysis (NMA) has been performed yet to compare all available interventions. Therefore, the present research project aims to investigate the impact of different nutrition interventions in the school setting by comparing and ranking them using NMA methodology.!##!Methods/design!#!A systematic literature search will be performed in 11 electronic databases (PubMed, the Cochrane Library, Web of Science, ERIC, PsycINFO, CAB Abstracts, Campbell Library, BiblioMap EPPI, Australian Education Index, Joanna Briggs Institute Evidence-Based Practice Database and Practice-based Evidence in Nutrition Database). Parallel or cluster randomized controlled trials (RCTs) meeting the following criteria will be included: (1) generally healthy school students aged 4-18 years, (2) school-based intervention with ≥ 1 nutrition component, and (3) assessed anthropometric (overweight/obesity risk, body weight change, weight Z-score, [standardized] body mass index, body fat, waist circumference) and/or diet-quality measures (daily intake of fruits and vegetables, fat, and sugar-sweetened beverages). Random effects pairwise and NMA will be performed for these outcomes and surface under the cumulative ranking curve (SUCRA) estimated (P-score). Where possible, component NMA (CNMA) will be used additionally. Subgroup analyses are carried out for intervention duration, gender, age of school students, socioeconomic status, and geographical location, and sensitivity analyses by excluding high risk of bias RCTs.!##!Discussion!#!This systematic review and NMA will be the first to both directly and indirectly compare and rank different school-based nutrition interventions for the primary prevention of overweight and obesity in childhood and adolescence. Our analyses will provide important insights about the effects of the different interventions and show which are the most promising. The results of our study can help inform the design of new studies and will be of value to anyone interested in developing successful, evidence-based nutrition interventions in school settings.!##!Systematic review registration!#!PROSPERO: CRD42020220451

Good test retest reproducibility for an instrument to capture self-reported melanoma risk factors

Objective: To examine the test-retest reliability and validity of self-reported items capturing phenotypic characteristics and sun exposure measures in the baseline survey instrument used for a prospective study of skin cancer and melanoma

Overview of analysis steps in automated actinic keratosis detection, as applied to the dorsum of hand with the contrast adjusted for visualization.

<p>A) Input image. B) YCbCr transform of input image. C) Mean of Cb and Cr channels shows distinct hotspots for erythema. D) Guided filtering to remove unneeded texture. E) Distinct peaks extracted by morphological analysis. F) Hysteresis thresholding to identify erythematic areas. G) Boundaries of automatically detected lesions (white) compared with the dermatologist’s annotations (blue). </p

Confusion between automated/dermatologist assessment and the first and second dermatologist assessments on the face and arms.

<p>Confusion between automated/dermatologist assessment and the first and second dermatologist assessments on the face and arms.</p

Comparison of automatically detected lesions with dermatologist circumscribed lesions for each body site.

<p>Each point represents the total count for each method from one clinical photograph in the severe photodamage group. Labelled points correspond to photographs shown. White outlines are automatically detected regions, blue/green outlines are dermatologist annotations. A) Automatically counted lesions on each face photograph compared with dermatologist count, and number of co-localized lesions. B) Dermatologist second count on faces compared with first count, and number of co-localized lesions. C-D) Example of automated output compared with dermatologist on two foreheads. E) Automatically counted lesions on each arm photograph compared with dermatologist count, and number of co-localized lesions. F) Dermatologist second count on arms compared with first count, and number of co-localized lesions. G-H) Example of automated output compared with dermatologist annotation on forearm and hand. </p

Impact of different parameters on automatically identified actinic keratosis lesions.

<p>A-C) The texture regularization parameter ϵ controls how smooth the detected lesions boundaries are. D-F) The radius of the disc used in morphological opening by reconstruction controls the size of detected lesions. G-I) The high hysteresis threshold controls whether or not a potential lesion is included based on the maximum erythema intensity. </p

Knee pain during the first three months after unilateral total knee arthroplasty: A multi-centre prospective cohort study

Many patients have an unfavourable pain outcome post total knee arthroplasty (TKA). This multi-centre prospective cohort study recorded weekly pain scores one week before TKA and 12 weeks post TKA. 96 patients were enrolled into the study. Patients kept a record of their weekly scores pre-operation and post-operation by using the visual acuity score. Pain was divided into "best" pain score (lowest pain score) and "worst" pain score (highest pain score). Patients with a pre-operative pain scores ≤. 4 were identified as an at risk group for poor pain outcome. Female gender, age and anaesthetics type were not identified as risk factors for poor pain outcome. Pain trajectory analysis also identified general patterns of pain response post TKA