Opinion
EDITORIAL
The Recognition Process in Dermoscopy Analytic Approach vs Heuristic Approach Alon Scope, MD; Ralph P. Braun, MD
The 2-step algorithm in dermosopy was initially developed for the diagnosis of melanoma: The first step aims to decide whether the lesion is a melanocytic or nonmelanocytic neoplasm; the clinician seeks the presence of diagnostic criteRelated article ria for a melanocytic neoplasm (network, aggregated globules or streaks) or for a specific nonmelanocytic neoplasm (eg, basal cell carcinoma [BCC]). If the lesion does not fit any of the specific diagnoses, then, by default, one has to suspect that the lesion is nonetheless melanocytic in origin so as not to miss featureless melanoma. If the lesion is deemed to be melanocytic, one proceeds to the second step to decide whether it is a nevus or melanoma. Several diagnostic algorithms, including the ABCDE (asymmetry, border, color, diameter, elevation) rule, Menzies’ scoring method, the 7-point checklist, pattern analysis and CASH (color, architecture, symmetry, and homogeneity) algorithm, have been published. While the 2-step algorithm is imperfect,1 it can be easily taught to novices as a starting point for developing a personalized approach to diagnosis. The 2-step algorithm has further evolved with the advent of polarized dermoscopy and has incorporated vascular criteria into the first and second steps.2 The reproducibility among experts of the criteria used in the 2-step algorithm has also been tested.3
The 2-Step Algorithm The 2-step algorithm exemplifies a nonanalytic or heuristic approach. The term heuristic refers to experience-based techniques for problem solving and learning. With experience, one is able to rapidly identify recurrent patterns as specific entities without resorting to a detailed analysis. In addition, the 2-step algorithm uses metaphoric terms to describe dermoscopic structures (eg, “leaflike structures”). Metaphoric terms denote a structure based on a perceived visual similarity to an unrelated object and are commonly used in teaching to help assimilate new and unfamiliar concepts by associating them to objects more familiar to students. Metaphoric terms are widely used in clinical reasoning in medicine.4,5
The Analytic Approach More recently, Kittler6 proposed an analytic approach to dermoscopic diagnosis, in which descriptive terms are based on 5 basic geometric elements, namely, lines, pseudopods, circles, clods, dots, and structureless pattern. Pigmented lesions are described on the basis of the patterns and colors created by the geometric shapes. In addition, a set of dermoscopic structures constitute clues for specific diagnosis (eg, dermoscopijamadermatology.com
cally recognized gray circles in a lesion located on the head and neck is a clue for melanoma).7 The final diagnosis is based on the combination of the pattern of geometric shapes, colors and clues. Aside from “pseudopods” and “clods,” the analytic method avoids metaphoric terms.
Comparison of the 2 Methods In this Editorial, we have taken the role of self-appointed referees in the debate as to which approach is better, the 2-step algorithm or the analytic method. For disclosure, one of us (R.P.B.) is an advocate of the use of the 2-step algorithm.8 First, let’s illustrate a principal difference in the approach to diagnosis between the 2 methods. The 2-step algorithm can be considered a “top-to-bottom” approach, which means that we evaluate the entire lesion and interpret structures in the context of the lesion, while the analytic method would be considered a “bottom-up” approach, which means that we start from the 5 basic elements and end up with a diagnosis. An analogy to the difference between these approaches would be describing an elephant: A child would probably recognize the elephant immediately and, if asked why this is an elephant, would explain in a “top-to-bottom” approach that it has a trunk, 2 tusks, 4 thick legs, and a large body. This is the rapid and natural way to recognize an elephant. By this method, if we needed to teach a novice what an elephant is, we would simply show more illustrative examples highlighting the common reproducible features. However, computer-vision trying to identify an elephant would probably use a “bottom-up” approach, first detecting that this animal has thick curved line (trunk), 2 shorter curved lines on the sides (tusks), thin straight line (tail), 4 pseudopods (legs), 2 black dots (eyes), and a large clod (body), and then putting this array together as most fitting an elephant. Second, let’s consider when each method could be advantageous. In the busy practice, an experienced clinician examining multiple skin lesions with dermoscopy is under time constraints and would be inclined to use a heuristic approach— rapid recognition of lesions by pattern.9 Indeed, under time pressure and cognitive load, clinicians tend to make decisions based on an heuristic approach.10 Because most lesions seen in practice display recurrent patterns and structures, the 2-step algorithm can be easily memorized and applied in daily practice.9 However, when the lesions in question does not fit any rapidly recognized pattern, the clinician would pause to analyze it. When analyzing the lesion, the clinician gathers detailed morphological information about the lesion, including its structures, colors, and distribution. For the 2-step algorithm, structures need to be recognized using specific metaphoric names that already (Reprinted) JAMA Dermatology Published online February 25, 2015
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://archderm.jamanetwork.com/ by a The University of Manchester Library User on 05/19/2015
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Opinion Editorial
imply a specific diagnosis (eg, if you say you're seeing a spokedwheel–like structure, you are already considering the diagnosis of BCC); admittedly, specific recognition of structures is sometimes difficult for novices. Going back to the elephant analogy, the heuristic approach would require experience because the elements are named in the context of the animal. If one has seen elephants, then one would recognize other elephants with little effort. However, the heuristic approach is difficult to apply if one has never seen a mammoth before, and all one would be able to do is to exclude that this is a chicken or a mouse, or state that this is reminiscent of an elephant. The analytical method, however, permits more generic description of colors and geometric structures without committing to a specific diagnosis during the descriptive process; only in the final integration of the data are the diagnoses rendered. That said, some clinicians advocate a rule of thumb for novices stating that if you pause to analyze a solitary lesion for too long (eg, for >10 seconds), then you should consider performing a biopsy of that lesion; back to the simple and practical rule, modified here “when in doubt, don't overanalyze, cut it out.” Third, how does each method perform when tested in a study? Proponents of the analytical method tested the accuracy of the first step of the 2-step algorithm aiming to evaluate the frequency of misclassifications of equivocal pigmented lesions as melanocytic vs nonmelanocytic.11 In total, 707 consecutive cases from 553 European and Australian patients were included. Among European patients, sensitivity for correct classification of melanocytic neoplasms was 97% and specificity, 68%. However, among Australian patients, who are characterized by sun-damaged skin, sensitivity was 97%, but specificity was only 34%; the authors11 noted that most common reasons for misclassification among these patients were the presence of a pigmented network in a nonmelanocytic lesion and the absence of specific dermoscopic features leading to classification of nonmelanocytic lesions as “melanocytic by default.” When tested by its proponents, the 2-step algorithm did quite well. Chen et al,12 in this issue of JAMA Dermatology, report the application of the 2-step algorithm to the diagnosis of 9168 lesions. The sensitivity for the diagnosis of melanoma was 85%; specificity, 94%; positive predictive value, 77%; negative predictive value, 97%; and diagnostic accu-
ARTICLE INFORMATION Author Affiliations: Department of Dermatology, Sheba Medical Center, Ramat Gan and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel (Scope); Department of Dermatology, University Hospital Zürich, Switzerland (Braun).
two-step dermoscopy algorithm. Dermatol Surg. 2006;32(11):1398-1406.
diagnosis of pigmented skin lesions. Dermatopathol: Pract Conc. 2007;13:1.
2. Marghoob AA, Braun R. Proposal for a revised 2-step algorithm for the classification of lesions of the skin using dermoscopy. Arch Dermatol. 2010; 146(4):426-428.
7. Kittler H, Rosendahl C, Cameron A, Tschandl P. Dermatoscopy. Vienna, Austria: Facultas WUV; 2011.
Corresponding Author: Ralph P. Braun, MD, Department of Dermatology, University Hospital Zürich, Gloriastrasse 31, 8091 Zürich, Switzerland ([email protected]).
3. Argenziano G, Soyer HP, Chimenti S, et al. Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol. 2003;48(5):679-693.
Published Online: February 25, 2015. doi:10.1001/jamadermatol.2014.4810.
4. Norman G. Building on experience--the development of clinical reasoning. N Engl J Med. 2006;355(21):2251-2252.
Conflict of Interest Disclosures: None reported REFERENCES 1. Scope A, Benvenuto-Andrade C, Agero AL, Marghoob AA. Nonmelanocytic lesions defying the
E2
racy, 93%. In addition, the analytic approach of Rosendahl et al13 has also tested 463 lesions and yielded sensitivity of 83%; specificity, 80%; and diagnostic accuracy, 89%; for the particular diagnosis of melanoma, sensitivity was found to be 80% Fourth, which method should be taught to novices? Tschandl et al14 performed a small study in which final-year medical students were given 1-hour dermoscopy training using either verbally based analytic teaching or an image-based heuristic teaching. The students were shown the same study set of 50 lesions (melanomas, BCCs, nevi, seborrheic keratoses, and dermatofibromas) before and after dermoscopy training. In both groups, training increased diagnostic accuracy increased by around 20%, regardless of the choice of the teaching method So, which method is better, analytic or heuristic? In our opinion, there is no “better” method. Both work, are not mutually exclusive but complementary, and can be applied in different scenarios. Recent literature on clinical diagnostic reasoning shows that analytic reasoning is the primary strategy for complex or ill-defined cases, unusual findings, or if the physician has had little clinical experience.4,5 Nonanalytic reasoning is essential in forming diagnostic expertise, and this skill is developed through clinical experience. Both nonanalytic and analytic reasoning strategies are effective and should be used simultaneously, in an interactive fashion. Indeed, recognizing the complementary nature of the heuristic and analytic methods, a collaborative group of dermoscopists who are working on this already. Finally, both methods are intrinsically limited because they are morphology based and require subjective interpretation of visual patterns. With experience, one realizes that clear morphological differentiation between benign and malignant neoplasms is not always possible. That being said, dermoscopic algorithms, be it the 2-step algorithm or the analytic method, are just part of the overall clinical diagnostic, which is more complex and can involve contextual information that is not incorporated into either dermoscopic algorithm.15 Final diagnosis and treatment decisions often take into account patient- and lesion-related factors, such as the patient’s age, risk factors for melanoma, history of changing lesion, and comparison of the lesion’s morphological characteristics to the patient’s other lesions.15
8. Braun RP, Rabinovitz HS, Oliviero M, Kopf AW, Saurat JH. Pattern analysis: a two-step procedure for the dermoscopic diagnosis of melanoma. Clin Dermatol. 2002;20(3):236-239. 9. Gachon J, Beaulieu P, Sei JF, et al. First prospective study of the recognition process of melanoma in dermatological practice. Arch Dermatol. 2005;141(4):434-438.
5. Bowen JL. Educational strategies to promote clinical diagnostic reasoning. N Engl J Med. 2006; 355(21):2217-2225.
10. Jaimes N, Dusza SW, Quigley EA, et al. Influence of time on dermoscopic diagnosis and management. Australas J Dermatol. 2013;54(2):96104.
6. Kittler H. Dermatoscopy: introduction of a new algorithmic method based on pattern analysis for
11. Tschandl P, Rosendahl C, Kittler H. Accuracy of the first step of the dermatoscopic 2-step algorithm
JAMA Dermatology Published online February 25, 2015 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://archderm.jamanetwork.com/ by a The University of Manchester Library User on 05/19/2015
jamadermatology.com
Editorial Opinion
for pigmented skin lesions. Dermatol Pract Concept. 2012;2(3):203a08. 12. Chen LL, Dusza SW, Jaimes N, Marghoob AA. Performance of the first step of the 2-step dermoscopy algorithm [published online February 25, 2015]. JAMA Dermatol. doi:10.1001 /jamadermatol.2014.4642.
jamadermatology.com
13. Rosendahl C, Tschandl P, Cameron A, Kittler H. Diagnostic accuracy of dermatoscopy for melanocytic and nonmelanocytic pigmented lesions. J Am Acad Dermatol. 2011;64(6):1068-1073. 14. Tschandl P, Kittler H, Schmid K, Zalaudek I, Argenziano G. Teaching dermatoscopy of pigmented skin tumours to novices: comparison of
analytic vs. heuristic approach [published online November 4, 2014]. J Eur Acad Dermatol Venereol. doi:10.1111/jdv.12790. 15. Marghoob AA, Scope A. The complexity of diagnosing melanoma. J Invest Dermatol. 2009;129 (1):11-13.
(Reprinted) JAMA Dermatology Published online February 25, 2015
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://archderm.jamanetwork.com/ by a The University of Manchester Library User on 05/19/2015
E3
EDITORIAL
The Recognition Process in Dermoscopy Analytic Approach vs Heuristic Approach Alon Scope, MD; Ralph P. Braun, MD
The 2-step algorithm in dermosopy was initially developed for the diagnosis of melanoma: The first step aims to decide whether the lesion is a melanocytic or nonmelanocytic neoplasm; the clinician seeks the presence of diagnostic criteRelated article ria for a melanocytic neoplasm (network, aggregated globules or streaks) or for a specific nonmelanocytic neoplasm (eg, basal cell carcinoma [BCC]). If the lesion does not fit any of the specific diagnoses, then, by default, one has to suspect that the lesion is nonetheless melanocytic in origin so as not to miss featureless melanoma. If the lesion is deemed to be melanocytic, one proceeds to the second step to decide whether it is a nevus or melanoma. Several diagnostic algorithms, including the ABCDE (asymmetry, border, color, diameter, elevation) rule, Menzies’ scoring method, the 7-point checklist, pattern analysis and CASH (color, architecture, symmetry, and homogeneity) algorithm, have been published. While the 2-step algorithm is imperfect,1 it can be easily taught to novices as a starting point for developing a personalized approach to diagnosis. The 2-step algorithm has further evolved with the advent of polarized dermoscopy and has incorporated vascular criteria into the first and second steps.2 The reproducibility among experts of the criteria used in the 2-step algorithm has also been tested.3
The 2-Step Algorithm The 2-step algorithm exemplifies a nonanalytic or heuristic approach. The term heuristic refers to experience-based techniques for problem solving and learning. With experience, one is able to rapidly identify recurrent patterns as specific entities without resorting to a detailed analysis. In addition, the 2-step algorithm uses metaphoric terms to describe dermoscopic structures (eg, “leaflike structures”). Metaphoric terms denote a structure based on a perceived visual similarity to an unrelated object and are commonly used in teaching to help assimilate new and unfamiliar concepts by associating them to objects more familiar to students. Metaphoric terms are widely used in clinical reasoning in medicine.4,5
The Analytic Approach More recently, Kittler6 proposed an analytic approach to dermoscopic diagnosis, in which descriptive terms are based on 5 basic geometric elements, namely, lines, pseudopods, circles, clods, dots, and structureless pattern. Pigmented lesions are described on the basis of the patterns and colors created by the geometric shapes. In addition, a set of dermoscopic structures constitute clues for specific diagnosis (eg, dermoscopijamadermatology.com
cally recognized gray circles in a lesion located on the head and neck is a clue for melanoma).7 The final diagnosis is based on the combination of the pattern of geometric shapes, colors and clues. Aside from “pseudopods” and “clods,” the analytic method avoids metaphoric terms.
Comparison of the 2 Methods In this Editorial, we have taken the role of self-appointed referees in the debate as to which approach is better, the 2-step algorithm or the analytic method. For disclosure, one of us (R.P.B.) is an advocate of the use of the 2-step algorithm.8 First, let’s illustrate a principal difference in the approach to diagnosis between the 2 methods. The 2-step algorithm can be considered a “top-to-bottom” approach, which means that we evaluate the entire lesion and interpret structures in the context of the lesion, while the analytic method would be considered a “bottom-up” approach, which means that we start from the 5 basic elements and end up with a diagnosis. An analogy to the difference between these approaches would be describing an elephant: A child would probably recognize the elephant immediately and, if asked why this is an elephant, would explain in a “top-to-bottom” approach that it has a trunk, 2 tusks, 4 thick legs, and a large body. This is the rapid and natural way to recognize an elephant. By this method, if we needed to teach a novice what an elephant is, we would simply show more illustrative examples highlighting the common reproducible features. However, computer-vision trying to identify an elephant would probably use a “bottom-up” approach, first detecting that this animal has thick curved line (trunk), 2 shorter curved lines on the sides (tusks), thin straight line (tail), 4 pseudopods (legs), 2 black dots (eyes), and a large clod (body), and then putting this array together as most fitting an elephant. Second, let’s consider when each method could be advantageous. In the busy practice, an experienced clinician examining multiple skin lesions with dermoscopy is under time constraints and would be inclined to use a heuristic approach— rapid recognition of lesions by pattern.9 Indeed, under time pressure and cognitive load, clinicians tend to make decisions based on an heuristic approach.10 Because most lesions seen in practice display recurrent patterns and structures, the 2-step algorithm can be easily memorized and applied in daily practice.9 However, when the lesions in question does not fit any rapidly recognized pattern, the clinician would pause to analyze it. When analyzing the lesion, the clinician gathers detailed morphological information about the lesion, including its structures, colors, and distribution. For the 2-step algorithm, structures need to be recognized using specific metaphoric names that already (Reprinted) JAMA Dermatology Published online February 25, 2015
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://archderm.jamanetwork.com/ by a The University of Manchester Library User on 05/19/2015
E1
Opinion Editorial
imply a specific diagnosis (eg, if you say you're seeing a spokedwheel–like structure, you are already considering the diagnosis of BCC); admittedly, specific recognition of structures is sometimes difficult for novices. Going back to the elephant analogy, the heuristic approach would require experience because the elements are named in the context of the animal. If one has seen elephants, then one would recognize other elephants with little effort. However, the heuristic approach is difficult to apply if one has never seen a mammoth before, and all one would be able to do is to exclude that this is a chicken or a mouse, or state that this is reminiscent of an elephant. The analytical method, however, permits more generic description of colors and geometric structures without committing to a specific diagnosis during the descriptive process; only in the final integration of the data are the diagnoses rendered. That said, some clinicians advocate a rule of thumb for novices stating that if you pause to analyze a solitary lesion for too long (eg, for >10 seconds), then you should consider performing a biopsy of that lesion; back to the simple and practical rule, modified here “when in doubt, don't overanalyze, cut it out.” Third, how does each method perform when tested in a study? Proponents of the analytical method tested the accuracy of the first step of the 2-step algorithm aiming to evaluate the frequency of misclassifications of equivocal pigmented lesions as melanocytic vs nonmelanocytic.11 In total, 707 consecutive cases from 553 European and Australian patients were included. Among European patients, sensitivity for correct classification of melanocytic neoplasms was 97% and specificity, 68%. However, among Australian patients, who are characterized by sun-damaged skin, sensitivity was 97%, but specificity was only 34%; the authors11 noted that most common reasons for misclassification among these patients were the presence of a pigmented network in a nonmelanocytic lesion and the absence of specific dermoscopic features leading to classification of nonmelanocytic lesions as “melanocytic by default.” When tested by its proponents, the 2-step algorithm did quite well. Chen et al,12 in this issue of JAMA Dermatology, report the application of the 2-step algorithm to the diagnosis of 9168 lesions. The sensitivity for the diagnosis of melanoma was 85%; specificity, 94%; positive predictive value, 77%; negative predictive value, 97%; and diagnostic accu-
ARTICLE INFORMATION Author Affiliations: Department of Dermatology, Sheba Medical Center, Ramat Gan and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel (Scope); Department of Dermatology, University Hospital Zürich, Switzerland (Braun).
two-step dermoscopy algorithm. Dermatol Surg. 2006;32(11):1398-1406.
diagnosis of pigmented skin lesions. Dermatopathol: Pract Conc. 2007;13:1.
2. Marghoob AA, Braun R. Proposal for a revised 2-step algorithm for the classification of lesions of the skin using dermoscopy. Arch Dermatol. 2010; 146(4):426-428.
7. Kittler H, Rosendahl C, Cameron A, Tschandl P. Dermatoscopy. Vienna, Austria: Facultas WUV; 2011.
Corresponding Author: Ralph P. Braun, MD, Department of Dermatology, University Hospital Zürich, Gloriastrasse 31, 8091 Zürich, Switzerland ([email protected]).
3. Argenziano G, Soyer HP, Chimenti S, et al. Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol. 2003;48(5):679-693.
Published Online: February 25, 2015. doi:10.1001/jamadermatol.2014.4810.
4. Norman G. Building on experience--the development of clinical reasoning. N Engl J Med. 2006;355(21):2251-2252.
Conflict of Interest Disclosures: None reported REFERENCES 1. Scope A, Benvenuto-Andrade C, Agero AL, Marghoob AA. Nonmelanocytic lesions defying the
E2
racy, 93%. In addition, the analytic approach of Rosendahl et al13 has also tested 463 lesions and yielded sensitivity of 83%; specificity, 80%; and diagnostic accuracy, 89%; for the particular diagnosis of melanoma, sensitivity was found to be 80% Fourth, which method should be taught to novices? Tschandl et al14 performed a small study in which final-year medical students were given 1-hour dermoscopy training using either verbally based analytic teaching or an image-based heuristic teaching. The students were shown the same study set of 50 lesions (melanomas, BCCs, nevi, seborrheic keratoses, and dermatofibromas) before and after dermoscopy training. In both groups, training increased diagnostic accuracy increased by around 20%, regardless of the choice of the teaching method So, which method is better, analytic or heuristic? In our opinion, there is no “better” method. Both work, are not mutually exclusive but complementary, and can be applied in different scenarios. Recent literature on clinical diagnostic reasoning shows that analytic reasoning is the primary strategy for complex or ill-defined cases, unusual findings, or if the physician has had little clinical experience.4,5 Nonanalytic reasoning is essential in forming diagnostic expertise, and this skill is developed through clinical experience. Both nonanalytic and analytic reasoning strategies are effective and should be used simultaneously, in an interactive fashion. Indeed, recognizing the complementary nature of the heuristic and analytic methods, a collaborative group of dermoscopists who are working on this already. Finally, both methods are intrinsically limited because they are morphology based and require subjective interpretation of visual patterns. With experience, one realizes that clear morphological differentiation between benign and malignant neoplasms is not always possible. That being said, dermoscopic algorithms, be it the 2-step algorithm or the analytic method, are just part of the overall clinical diagnostic, which is more complex and can involve contextual information that is not incorporated into either dermoscopic algorithm.15 Final diagnosis and treatment decisions often take into account patient- and lesion-related factors, such as the patient’s age, risk factors for melanoma, history of changing lesion, and comparison of the lesion’s morphological characteristics to the patient’s other lesions.15
8. Braun RP, Rabinovitz HS, Oliviero M, Kopf AW, Saurat JH. Pattern analysis: a two-step procedure for the dermoscopic diagnosis of melanoma. Clin Dermatol. 2002;20(3):236-239. 9. Gachon J, Beaulieu P, Sei JF, et al. First prospective study of the recognition process of melanoma in dermatological practice. Arch Dermatol. 2005;141(4):434-438.
5. Bowen JL. Educational strategies to promote clinical diagnostic reasoning. N Engl J Med. 2006; 355(21):2217-2225.
10. Jaimes N, Dusza SW, Quigley EA, et al. Influence of time on dermoscopic diagnosis and management. Australas J Dermatol. 2013;54(2):96104.
6. Kittler H. Dermatoscopy: introduction of a new algorithmic method based on pattern analysis for
11. Tschandl P, Rosendahl C, Kittler H. Accuracy of the first step of the dermatoscopic 2-step algorithm
JAMA Dermatology Published online February 25, 2015 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://archderm.jamanetwork.com/ by a The University of Manchester Library User on 05/19/2015
jamadermatology.com
Editorial Opinion
for pigmented skin lesions. Dermatol Pract Concept. 2012;2(3):203a08. 12. Chen LL, Dusza SW, Jaimes N, Marghoob AA. Performance of the first step of the 2-step dermoscopy algorithm [published online February 25, 2015]. JAMA Dermatol. doi:10.1001 /jamadermatol.2014.4642.
jamadermatology.com
13. Rosendahl C, Tschandl P, Cameron A, Kittler H. Diagnostic accuracy of dermatoscopy for melanocytic and nonmelanocytic pigmented lesions. J Am Acad Dermatol. 2011;64(6):1068-1073. 14. Tschandl P, Kittler H, Schmid K, Zalaudek I, Argenziano G. Teaching dermatoscopy of pigmented skin tumours to novices: comparison of
analytic vs. heuristic approach [published online November 4, 2014]. J Eur Acad Dermatol Venereol. doi:10.1111/jdv.12790. 15. Marghoob AA, Scope A. The complexity of diagnosing melanoma. J Invest Dermatol. 2009;129 (1):11-13.
(Reprinted) JAMA Dermatology Published online February 25, 2015
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://archderm.jamanetwork.com/ by a The University of Manchester Library User on 05/19/2015
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