Journal: The Cochrane Database of Systematic Reviews

Article Title: Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

doi: 10.1002/14651858.CD011902.pub2

Figure Lengend Snippet: Comparison of visual inspection and dermoscopy for detection of invasive melanoma or atypical intraepidermal melanocytic variants

Article Snippet: Index tests , Dermoscopy: new algorithm Method of diagnosis: for training set dermoscopic images were projected onto a screen; method NR for test set (assumed same procedures followed) Prior test data: no further information used Diagnostic threshold : significance of '8 clues of malignancy' ( Braun‐Falco 1990 ) were investigated in data collected 1989‐1990. A subset of relevant components were identified and evaluated on the test set of lesions (appears to be presence of any one considered test positive): asymmetrical pigment distribution, > 3 colours, asymmetrical depigmentation, black pigment, sharp pigment border and atypical radial streaming Diagnosis based on : single observer (n = 1) Observer qualifications: NR, likely dermatologist ("one of the authors") Experience in practice : not described Experience with dermoscopy : not described Derivation aspect: the 8 clues of malignancy were graded from 0 (absent) to 3 (distinct) on the test set of lesions (including asymmetrical pigment distribution, > 3 colours, black‐brown pigment, dark brown pigment, prominent pigment network, asymmetrical depigmentation, peripheral stripes, sharp pigment border and atypical radial streaming). Stepwise logistical regression used to select the variables that resulted in the best model for identification of melanoma , , .

Techniques: Comparison, Diagnostic Assay

Journal: The Cochrane Database of Systematic Reviews

Article Title: Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

doi: 10.1002/14651858.CD011902.pub2

Figure Lengend Snippet: Sensitivity analyses for image‐based visual inspection or dermoscopy for the detection of invasive melanoma or atypical intraepidermal melanocytic variants

Article Snippet: Index tests , Dermoscopy: new algorithm Method of diagnosis: for training set dermoscopic images were projected onto a screen; method NR for test set (assumed same procedures followed) Prior test data: no further information used Diagnostic threshold : significance of '8 clues of malignancy' ( Braun‐Falco 1990 ) were investigated in data collected 1989‐1990. A subset of relevant components were identified and evaluated on the test set of lesions (appears to be presence of any one considered test positive): asymmetrical pigment distribution, > 3 colours, asymmetrical depigmentation, black pigment, sharp pigment border and atypical radial streaming Diagnosis based on : single observer (n = 1) Observer qualifications: NR, likely dermatologist ("one of the authors") Experience in practice : not described Experience with dermoscopy : not described Derivation aspect: the 8 clues of malignancy were graded from 0 (absent) to 3 (distinct) on the test set of lesions (including asymmetrical pigment distribution, > 3 colours, black‐brown pigment, dark brown pigment, prominent pigment network, asymmetrical depigmentation, peripheral stripes, sharp pigment border and atypical radial streaming). Stepwise logistical regression used to select the variables that resulted in the best model for identification of melanoma , , .

Techniques: Diagnostic Assay

Journal: The Cochrane Database of Systematic Reviews

Article Title: Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

doi: 10.1002/14651858.CD011902.pub2

Figure Lengend Snippet: Comparison of visual inspection and dermoscopy for the detection of invasive melanoma

Article Snippet: Index tests , Dermoscopy: new algorithm Method of diagnosis: for training set dermoscopic images were projected onto a screen; method NR for test set (assumed same procedures followed) Prior test data: no further information used Diagnostic threshold : significance of '8 clues of malignancy' ( Braun‐Falco 1990 ) were investigated in data collected 1989‐1990. A subset of relevant components were identified and evaluated on the test set of lesions (appears to be presence of any one considered test positive): asymmetrical pigment distribution, > 3 colours, asymmetrical depigmentation, black pigment, sharp pigment border and atypical radial streaming Diagnosis based on : single observer (n = 1) Observer qualifications: NR, likely dermatologist ("one of the authors") Experience in practice : not described Experience with dermoscopy : not described Derivation aspect: the 8 clues of malignancy were graded from 0 (absent) to 3 (distinct) on the test set of lesions (including asymmetrical pigment distribution, > 3 colours, black‐brown pigment, dark brown pigment, prominent pigment network, asymmetrical depigmentation, peripheral stripes, sharp pigment border and atypical radial streaming). Stepwise logistical regression used to select the variables that resulted in the best model for identification of melanoma , , .

Techniques: Comparison, Diagnostic Assay

Journal: The Cochrane Database of Systematic Reviews

Article Title: Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

doi: 10.1002/14651858.CD011902.pub2

Figure Lengend Snippet: Comparison of visual inspection and dermoscopy for the detection of any skin lesion requiring excision

Article Snippet: Index tests , Dermoscopy: new algorithm Method of diagnosis: for training set dermoscopic images were projected onto a screen; method NR for test set (assumed same procedures followed) Prior test data: no further information used Diagnostic threshold : significance of '8 clues of malignancy' ( Braun‐Falco 1990 ) were investigated in data collected 1989‐1990. A subset of relevant components were identified and evaluated on the test set of lesions (appears to be presence of any one considered test positive): asymmetrical pigment distribution, > 3 colours, asymmetrical depigmentation, black pigment, sharp pigment border and atypical radial streaming Diagnosis based on : single observer (n = 1) Observer qualifications: NR, likely dermatologist ("one of the authors") Experience in practice : not described Experience with dermoscopy : not described Derivation aspect: the 8 clues of malignancy were graded from 0 (absent) to 3 (distinct) on the test set of lesions (including asymmetrical pigment distribution, > 3 colours, black‐brown pigment, dark brown pigment, prominent pigment network, asymmetrical depigmentation, peripheral stripes, sharp pigment border and atypical radial streaming). Stepwise logistical regression used to select the variables that resulted in the best model for identification of melanoma , , .

Techniques: Comparison, Diagnostic Assay

Journal: The Cochrane Database of Systematic Reviews

Article Title: Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

doi: 10.1002/14651858.CD011902.pub2

Figure Lengend Snippet: Summary of findings table

Article Snippet: Index tests , Dermoscopy: new algorithm Method of diagnosis: for training set dermoscopic images were projected onto a screen; method NR for test set (assumed same procedures followed) Prior test data: no further information used Diagnostic threshold : significance of '8 clues of malignancy' ( Braun‐Falco 1990 ) were investigated in data collected 1989‐1990. A subset of relevant components were identified and evaluated on the test set of lesions (appears to be presence of any one considered test positive): asymmetrical pigment distribution, > 3 colours, asymmetrical depigmentation, black pigment, sharp pigment border and atypical radial streaming Diagnosis based on : single observer (n = 1) Observer qualifications: NR, likely dermatologist ("one of the authors") Experience in practice : not described Experience with dermoscopy : not described Derivation aspect: the 8 clues of malignancy were graded from 0 (absent) to 3 (distinct) on the test set of lesions (including asymmetrical pigment distribution, > 3 colours, black‐brown pigment, dark brown pigment, prominent pigment network, asymmetrical depigmentation, peripheral stripes, sharp pigment border and atypical radial streaming). Stepwise logistical regression used to select the variables that resulted in the best model for identification of melanoma , , .

Techniques: Diagnostic Assay, Comparison, Biomarker Discovery, Selection, Histopathology

Journal: STAR Protocols

Article Title: Protocol to quantify immune cell distribution from the vasculature to the glioma microenvironment on sequential immunofluorescence multiplex images

doi: 10.1016/j.xpro.2024.103079

Figure Lengend Snippet:

Article Snippet: Timing: 24 h This part allows the user to train the Visiopharm machine learning algorithm while integrating the data into other modalities of analysis like R Studio and subsequently Spyder for more accurate results (cf. part 6).

Techniques: Recombinant, Imaging, Software

Journal: Current biology : CB

Article Title: Rat orbitofrontal ensemble activity contains multiplexed but dissociable representations of value and task structure in an odor sequence task

doi: 10.1016/j.cub.2019.01.048

Figure Lengend Snippet: (A) The firing rates of all single neurons on each trial constituted a high-dimensional vector (360 vectors or data points in a 1078- dimensional space). The firing rates of all neurons at the odor time were linearly projected to a principal component subspace with 80% variance explained, then to an LDA space with labels about the current reward. Each LDA component combined a weighted sum of inputs from all the neurons. The LDA transformation was supervised by trial-type labels that only separated current value (reward vs. non-reward) so that the LDA could find components that best separated the two classes. Comp., Component. (B) The first but not the second LDA component perfectly separated the two trial types (p = 1.0 × 10−3 and 1.0, respectively; two-sided permutation test, 1000 bootstrap samples). (C) An ROC-based value-selectivity index (2 × |AUC – 0.5|) ranging from 0 (low selectivity) to 1 (high selectivity) was used to test current value selectivity for each individual LDA component. The first LDA component showed perfect value selectivity (1.0; p = 1.0 × 10−3; permutation test; 1000 bootstrap samples). But, none of the remaining 150 LDA components were selective for the current value (< 0.05; p = 1.0 for all components; two-sided permutation test; 1000 bootstrap samples). (D) Value discriminability was used to test whether value was distributed across components (0 – 1 indicates the level of value discriminability by population components). The true discriminability was compared with that from the label-shuffled data. The first LDA component showed significantly higher value discriminability than the shuffled data (1.0 vs. 0.05; p = 1.0 × 10−3; one-sided permutation test; 1000 bootstrap samples), but the remaining LDA components did not show significantly higher value discriminability than the shuffled data (0.13 vs. 0.1; p = 1.0; one-sided permutation test; 1000 bootstrap samples). Curr. Val. Discrim., Current Value Discriminability. Error bars are standard deviations (SDs). (E) A dendrogram using all different LDA components contained both value and state information (left). A dendrogram that only used the first LDA component only contained value information without detailed state information (center), while a dendrogram that only used the remaining LDA components contained state information without current value (right). (F) Decoding of 24 states with the first LDA component (reconstructed to 151 PCs before the decoding analysis). (G) Comparison of decoding accuracy for each state (represented by each dot) between all LDA components and the first LDA component being used. Dec. Decoding; LCs, LDA Components. (H) Confusion matrix at odor time was binarized at thresholds 0%, 5%, and 20%. (I) Correlation coefficients compare the similarity between hypothesized “current value” and “current location” matrices and the actual confusion matrices (obtained by using the first LDA component) at different filtering thresholds. (J) Decoding of 24 states with the remaining 150 LDA components (reconstructed to 151 PCs). (K) Comparison of decoding accuracy for each state between all LDA components and the remaining LDA components (the first one was left out) being used. (L) Confusion matrix at odor time was binarized at thresholds 0%, 5%, and 20%. (M) Correlation coefficients compare the similarity between hypothesized “current value” and “current location” matrices and the actual confusion matrices (obtained by using the remaining LDA components) at different filtering thresholds.

Article Snippet: We trained a linear discriminant analysis (LDA) algorithm (MATLAB function: fitcdiscr ) to classify 24 trial types or locations for each one of six task events.

Techniques: Plasmid Preparation, Transformation Assay, Comparison