PERFORM Publications

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Title		Authors	PubMed ID
1	Tuning Deep Learning for Predicting Aluminum Prices Under Different Sampling: Bayesian Optimization Versus Random Search	Alicia Estefania Antonio Figueroa	41751647 CONCORDIA
2	ADPv2: A hierarchical histological tissue type-annotated dataset for potential biomarker discovery of colorectal disease	Yang Z; Li K; Ramandi SG; Brassard P; Khellaf A; Trinh VQ; Zhang J; Chen L; Rowsell C; Varma S; Plataniotis K; Hosseini MS;	41658283 ENCS
3	A Deep Learning-Based Ensemble System for Brent and WTI Crude Oil Price Analysis and Prediction	Zhang Y; Lahmiri S;	41294965 JMSB
4	Attention-Fusion-Based Two-Stream Vision Transformer for Heart Sound Classification	Ranipa K; Zhu WP; Swamy MNS;	41155032 ENCS
5	Lung Nodule Malignancy Classification Integrating Deep and Radiomic Features in a Three-Way Attention-Based Fusion Module	Khademi S; Heidarian S; Afshar P; Mohammadi A; Sidiqi A; Nguyen ET; Ganeshan B; Oikonomou A;	41150036 ENCS
6	Deep learning-based feature discovery for decoding phenotypic plasticity in pediatric high-grade gliomas single-cell transcriptomics	Abicumaran Uthamacumaran	40848317 PSYCHOLOGY
7	Artificial intelligence-assisted identification of condensing osteitis and idiopathic osteosclerosis on panoramic radiographs	Yuksel IB; Boudesh A; Ghanbarzadehchaleshtori M; Ozsoy SC; Bahrilli S; Mohammadi R; Altindag A;	40790082 ENCS
8	Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations	Gharamaleki SK; Helfield B; Rivaz H;	40640235 PHYSICS
9	Comprehensive review of reinforcement learning for medical ultrasound imaging	Elmekki H; Islam S; Alagha A; Sami H; Spilkin A; Zakeri E; Zanuttini AM; Bentahar J; Kadem L; Xie WF; Pibarot P; Mizouni R; Otrok H; Singh S; Mourad A;	40567264 ENCS
10	CASCADE-FSL: Few-shot learning for collateral evaluation in ischemic stroke	Aktar M; Tampieri D; Xiao Y; Rivaz H; Kersten-Oertel M;	40250214 ENCS
11	Large language models deconstruct the clinical intuition behind diagnosing autism	Stanley J; Rabot E; Reddy S; Belilovsky E; Mottron L; Bzdok D;	40147442 ENCS
12	Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models	Gheflati B; Mirzaei M; Rottoo S; Rivaz H;	39953355 ENCS
13	In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability	Khaked AA; Oishi N; Roggen D; Lago P;	39860799 ENCS
14	A protocol for trustworthy EEG decoding with neural networks	Borra D; Magosso E; Ravanelli M;	39549492 ENCS
15	Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks	Adcock B; Brugiapaglia S; Dexter N; Moraga S;	39454372 MATHSTATS
16	Deep neural network-based robotic visual servoing for satellite target tracking	Ghiasvand S; Xie WF; Mohebbi A;	39440297 ENCS
17	SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals	Borra D; Paissan F; Ravanelli M;	39265481 ENCS
18	Exploiting protein language models for the precise classification of ion channels and ion transporters	Ghazikhani H; Butler G;	38656743 CSFG
19	SCANED: Siamese collateral assessment network for evaluation of collaterals from ischemic damage	Aktar M; Xiao Y; Tehrani AKZ; Tampieri D; Rivaz H; Kersten-Oertel M;	38364600 ENCS
20	The State of Artificial Intelligence in Skin Cancer Publications	Joly-Chevrier M; Nguyen AX; Liang L; Lesko-Krleza M; Lefrançois P;	38323537 ENCS
21	Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine	Salimi M; Roshanfar M; Tabatabaei N; Mosadegh B;	38248734 ENCS
22	Deep learning for tooth identification and enumeration in panoramic radiographs	Sadr S; Mohammad-Rahimi H; Ghorbanimehr MS; Rokhshad R; Abbasi Z; Soltani P; Moaddabi A; Shahab S; Rohban MH;	38169618 ENCS
23	Editorial: Computational systems immunovirology	Zarei Ghobadi M; Teymoori-Rad M; Selvaraj G; Wei DQ;	37475870 CHEMBIOCHEM
24	Prospects of Novel and Repurposed Immunomodulatory Drugs against Acute Respiratory Distress Syndrome (ARDS) Associated with COVID-19 Disease	Nayak SS; Naidu A; Sudhakaran SL; Vino S; Selvaraj G;	37109050 CHEMBIOCHEM
25	Compatible-domain Transfer Learning for Breast Cancer Classification with Limited Annotated Data	Shamshiri MA; Krzyzak A; Kowal M; Korbicz J;	36758326 ENCS
26	Deep learning approach to security enforcement in cloud workflow orchestration	El-Kassabi HT; Serhani MA; Masud MM; Shuaib K; Khalil K;	36691661 ENCS
27	UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection	Abdar M; Salari S; Qahremani S; Lam HK; Karray F; Hussain S; Khosravi A; Acharya UR; Makarenkov V; Nahavandi S;	36217534 ENCS
28	A Deep Learning Approach to Capture the Essence of Candida albicans Morphologies	Bettauer V; Costa ACBP; Omran RP; Massahi S; Kirbizakis E; Simpson S; Dumeaux V; Law C; Whiteway M; Hallett MT;	35972285 BIOLOGY
29	The Smart in Smart Cities: A Framework for Image Classification Using Deep Learning	Al-Qudah R; Khamayseh Y; Aldwairi M; Khan S;	35746171 ENCS
30	Deep reconstruction of high-quality ultrasound images from raw plane-wave data: A simulation and in vivo study	Goudarzi S; Rivaz H;	35728310 ENCS
31	Knowledge distillation approach towards melanoma detection	Khan MS; Alam KN; Dhruba AR; Zunair H; Mohammed N;	35594685 CONCORDIA
32	Weakly Supervised Occupancy Prediction Using Training Data Collected via Interactive Learning	Bouhamed O; Amayri M; Bouguila N;	35590880 ENCS
33	Energy migration control of multi-modal emissions in an Er3+ doped nanostructure toward information encryption and deep learning decoding	Song Y; Lu M; Mandl GA; Xie Y; Sun G; Chen J; Liu X; Capobianco JA; Sun L;	34476872 ENCS
34	COVID-FACT: A Fully-Automated Capsule Network-Based Framework for Identification of COVID-19 Cases from Chest CT Scans	Heidarian S; Afshar P; Enshaei N; Naderkhani F; Rafiee MJ; Babaki Fard F; Samimi K; Atashzar SF; Oikonomou A; Plataniotis KN; Mohammadi A;	34113843 ENCS
35	Corrigendum: Deep Learning-Based Haptic Guidance for Surgical Skills Transfer	Fekri P; Dargahi J; Zadeh M;	34026860 ENCS
36	Deep Learning-Based Haptic Guidance for Surgical Skills Transfer.	Fekri P, Dargahi J, Zadeh M	33553246 ENCS
37	COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images.	Afshar P, Heidarian S, Naderkhani F, Oikonomou A, Plataniotis KN, Mohammadi A	32958971 ENCS

Title:	The State of Artificial Intelligence in Skin Cancer Publications
Authors:	Joly-Chevrier M, Nguyen AX, Liang L, Lesko-Krleza M, Lefrançois P
Link:	https://pubmed.ncbi.nlm.nih.gov/38323537/
DOI:	10.1177/12034754241229361
Publication:	Journal of cutaneous medicine and surgery
Keywords:	artificial intelligence; bibliometric; deep learning; machine learning; skin cancer;
PMID:	38323537	Category:	Date Added:	2024-02-07
Dept Affiliation:	ENCS 1 Faculty of Medicine, Université de Montréal, Montreal, QC, Canada. 2 Department of Ophthalmology, University of Toronto, Toronto, ON, Canada. 3 Faculty of Engineering, McGill University, Montreal, QC, Canada. 4 Division of Computer Engineering, Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada. 5 Division of Dermatology, Department of Medicine, McGill University, Montreal, QC, Canada. 6 Division of Dermatology, Department of Medicine, Jewish General Hospital, Montreal, QC, Canada. 7 Lady Davis Institute for Medical Research, Montreal, QC, Canada.

Description:

Background: Artificial intelligence (AI) in skin cancer is a promising research field to assist physicians and to provide support to patients remotely. Physicians' awareness to new developments in AI research is important to define the best practices and scope of integrating AI-enabled technologies within a clinical setting.

Objectives: To analyze the characteristics and trends of AI skin cancer publications from dermatology journals.

Methods: AI skin cancer publications were retrieved in June 2022 from the Web of Science. Publications were screened by title, abstract, and keywords to assess eligibility. Publications were fully reviewed. Publications were divided between nonmelanoma skin cancer (NMSC), melanoma, and skin cancer studies. The primary measured outcome was the number of citations. The secondary measured outcomes were articles' general characteristics and features related to AI.

Results: A total of 168 articles were included: 25 on NMSC, 77 on melanoma, and 66 on skin cancer. The most common types of skin cancers were melanoma (134, 79.8%), basal cell carcinoma (61, 36.3%), and squamous cell carcinoma (45, 26.9%). All articles were published between 2000 and 2022, with 49 (29.2%) of them being published in 2021. Original studies that developed or assessed an algorithm predominantly used supervised learning (66, 97.0%) and deep neural networks (42, 67.7%). The most used imaging modalities were standard dermoscopy (76, 45.2%) and clinical images (39, 23.2%).

Conclusions: Most publications focused on developing or assessing screening technologies with mainly deep neural network algorithms. This indicates the eminent need for dermatologists to label or annotate images used by novel AI systems.

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