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Article ; Online: Clinical and laboratory profile of patients with Kyasanur forest disease: A single-centre study of 192 patients from Karnataka, India.

Gupta, Nitin / Chunduru, Kiran / Safeer K, Mohammad / Saravu, Kavitha

Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology

2021 Volume 135, Page(s) 104735

Abstract: Introduction: Kyasanur forest disease (KFD) is a biphasic tick-borne viral fever that is endemic to 16 districts and five states of Southern India. The aim of this study was to describe the clinical/ laboratory manifestations of KFD.: Materials and ... ...

Abstract	Introduction: Kyasanur forest disease (KFD) is a biphasic tick-borne viral fever that is endemic to 16 districts and five states of Southern India. The aim of this study was to describe the clinical/ laboratory manifestations of KFD. Materials and methods: This is a retrospective cohort study of confirmed KFD patients admitted in our hospital between December 2018 and June 2019. The demographic, clinical and laboratory parameters of patients during the first and second phase of illness was recorded in a pre-defined case study form. Results: A total of 192 patients from Karnataka were diagnosed with a mean age of 46.2 ± 15.6 years and a male preponderance (57 %). Fever (99 %), myalgia (52 %), headache (43 %), cough (14 %), conjunctival congestion (14 %), altered sensorium (13 %) and haemorrhagic manifestations (8%) were seen in the first phase. A total of 18 % of the patients came back with a second febrile episode. The features of meningoencephalitis were seen in 34 % of the patients during the second phase. Leucopenia, thrombocytopenia, and increase in liver enzymes, creatine phosphokinase (CPK) and activated partial thromboplastin time (APTT) was seen in the first phase but not in the second phase. Higher age, myocarditis, altered sensorium in the first phase, hypotension at admission, lower platelet count, elevated liver enzymes, higher APTT and CPK, were significantly associated with mortality. Conclusion: The primary care physicians or travel medicine practitioners should be aware of the distinct clinical and laboratory manifestations of KFD, including the ones that may signify requirements of higher levels of care.
MeSH term(s)	Adult ; Humans ; India/epidemiology ; Kyasanur Forest Disease/epidemiology ; Laboratories ; Male ; Middle Aged ; Retrospective Studies ; Tick-Borne Diseases
Language	English
Publishing date	2021-01-13
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1446080-4
ISSN	1873-5967 ; 1386-6532
ISSN (online)	1873-5967
ISSN	1386-6532
DOI	10.1016/j.jcv.2021.104735
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Article ; Online: Neurological manifestations of Kyasanur Forest disease: a retrospective cohort study from South India.

Gupta, Nitin / Nallapati, Vishnu Teja / Chunduru, Kiran / Vithivattical, Alphy Rose James / Kadavigere, Rajagopal / Saravu, Kavitha

Transactions of the Royal Society of Tropical Medicine and Hygiene

2022 Volume 116, Issue 10, Page(s) 944–948

Abstract: Background: Kyasanur Forest disease (KFD) is a viral zoonotic disease where patients present with febrile illness and haemorrhagic manifestations in the first phase. In a small fraction of patients, the fever may be biphasic. This study aimed to ... ...

Abstract	Background: Kyasanur Forest disease (KFD) is a viral zoonotic disease where patients present with febrile illness and haemorrhagic manifestations in the first phase. In a small fraction of patients, the fever may be biphasic. This study aimed to describe the neurological manifestations of patients with KFD in the first and second phases of the illness. Methods: This is a retrospective cohort study of 297 patients admitted with a molecular diagnosis of KFD from December 2018 to December 2020. The case records of these patients were reviewed for evidence of neurological involvement. Results: A total of 34 (11.5%) patients in the first phase and 16 (36.4%) patients in the second phase had neurological involvement. Altered sensorium, seizures and focal infarcts were common in the first phase, while cerebellar signs and leptomeningeal enhancement were common in the second phase. Conclusions: Neurological involvement is seen in both phases of KFD. While in the first phase it is a result of possible encephalitis/encephalopathy, the second phase involvement is possibly due to postinfectious cerebellitis or meningitis.
MeSH term(s)	Humans ; India/epidemiology ; Kyasanur Forest Disease/complications ; Kyasanur Forest Disease/epidemiology ; Retrospective Studies
Language	English
Publishing date	2022-02-28
Publishing country	England
Document type	Journal Article
ZDB-ID	441375-1
ISSN	1878-3503 ; 0035-9203
ISSN (online)	1878-3503
ISSN	0035-9203
DOI	10.1093/trstmh/trac018
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Article ; Online: Clinical, laboratory profile and molecular characterization of

Chunduru, Kiran / A R, Manoj / Poornima, Subhadra / Hande H, Manjunatha / Devaki, Ramakrishna / Varghese, George M / Saravu, Kavitha

Infectious diseases (London, England)

2023 Volume 56, Issue 3, Page(s) 220–229

Abstract: Background: Scrub typhus is a vector-borne infection caused by the obligate intracellular organism : Objective: To study the clinical and laboratory profiles of patients who succumbed to scrub typhus.: Methods: A prospective cohort study was ... ...

Abstract	Background: Scrub typhus is a vector-borne infection caused by the obligate intracellular organism Objective: To study the clinical and laboratory profiles of patients who succumbed to scrub typhus. Methods: A prospective cohort study was conducted from August 2019 through April 2023 on scrub typhus patients admitted to our hospital. Clinical and laboratory parameters of all the patients were recorded, and blood samples were drawn. To confirm scrub typhus, a nested polymerase chain reaction (nPCR) was performed in collected samples. Viable amplicons were sequenced, and phylogenetic analyses were performed to identify infecting genotypes. Results: A total of 261 patients were enrolled. Of these, nine (3.45%) patients succumbed at a median (Interquartile Range) duration of 5 (1.5, 10.5) days after admission. Sepsis with septic shock (9, 100%) and acute kidney injury (AKI) (6, 66%) were noted among the succumbed patients. All the succumbed patients (100%) required intensive care admission, inotropic and ventilatory support. While 5 (55%) patients required dialysis, two (22%) required blood transfusion. Three (33%) patient samples were co-positive for Conclusion: Delay in scrub typhus diagnosis can result in severe complications, septic shock, and multisystem organ failure, culminating in death.
MeSH term(s)	Humans ; Orientia tsutsugamushi/genetics ; Scrub Typhus/epidemiology ; Phylogeny ; Prospective Studies ; Shock, Septic/epidemiology ; Escherichia coli ; India/epidemiology ; Sepsis
Language	English
Publishing date	2023-12-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2839775-7
ISSN	2374-4243 ; 2374-4235
ISSN (online)	2374-4243
ISSN	2374-4235
DOI	10.1080/23744235.2023.2290106
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Article ; Online: Clinical, laboratory, and molecular epidemiology of Orientia tsutsugamushi infection from Southwestern India.

Chunduru, Kiran / A R, Manoj / Poornima, Subhadra / Hande H, Manjunatha / M, Mridula / Varghese, George M / Devaki, Ramakrishna / Saravu, Kavitha

PloS one

2023 Volume 18, Issue 7, Page(s) e0289126

Abstract: Scrub typhus is a vector borne disease which in a proportion of patients causes multiorgan involvement and death if untreated. Infecting genotype and virulence factors play a role in severity of infection and outcome. The current prospective cohort study ...

Abstract	Scrub typhus is a vector borne disease which in a proportion of patients causes multiorgan involvement and death if untreated. Infecting genotype and virulence factors play a role in severity of infection and outcome. The current prospective cohort study was undertaken to elucidate the severity of illness in scrub typhus patients and to identify the circulating genotypes in Karnataka, India. A total of 214 patients of either gender from 9 districts of Karnataka and one patient each from Andhra Pradesh and Kerala, India were enrolled in the study. With a predefined severity criterion, 132 patients were segregated to the severe group. Multi organ involvement was seen in 59 (44.69%) patients. Phylogenetic analysis revealed JG-v like (48.97%), Karp-like (26.53%), JG-like (22.44%), and Kato-like (2.04%) strains in Karnataka. Patients infected with Orientia tsutsugamushi Karp-like strains had respiratory involvement (69.2%), cardiovascular involvement (46.2%) and thrombocytopenia (23.1%) and required higher hospital resource utilization.
MeSH term(s)	Humans ; Scrub Typhus/epidemiology ; Orientia tsutsugamushi/genetics ; Molecular Epidemiology ; Phylogeny ; Prospective Studies ; India/epidemiology
Language	English
Publishing date	2023-07-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0289126
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Article: Validation of a Clinical Risk-scoring Algorithm for Scrub Typhus Severity in South India.

Gulati, Shivali / Chunduru, Kiran / Madiyal, Mridula / Setia, Maninder S / Saravu, Kavitha

Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine

2021 Volume 25, Issue 5, Page(s) 551–556

Abstract: ... Chunduru K, Madiyal M, Setia MS, Saravu K. Validation of a Clinical Risk-scoring Algorithm for Scrub Typhus ...

Abstract	Background: A clinical risk-scoring algorithm (CRSA) to forecast the scrub typhus severity was developed from two general hospitals in Thailand where patients were classified into three groups-nonsevere, severe, and fatal. In this study, an attempt was made to validate the risk-scoring algorithm for prognostication of scrub typhus severity in India. Materials and methods: This prospective study was conducted at a hospital in South India between November 2017 and March 2019. Patients of scrub typhus were categorized into nonsevere, severe, and fatal according to the CRSA. The patients were also grouped into severe and nonsevere according to the definition of severe scrub typhus which was used as a gold standard. The obtained CRSA score was validated against the classification based on the definition of severe scrub typhus. Receiver operating characteristics (ROC) curve for the scores was plotted and the Youden's index for optimal cutoff was used. Results: A total of 198 confirmed cases of scrub typhus were included in the study. According to the ROC curve, at a severity score ≥7, an optimal combination of sensitivity of 75.9% and specificity of 77.5% was achieved. It correctly predicted 76.77% (152 of 198) of patients as severe, with an underestimation of 10.61% (21 patients) and an overestimation of 12.63% (25 patients). Conclusion: In the present study setting, a cutoff of ≥7 for severity prediction provides an optimum combination of sensitivity and specificity. These findings need to be validated in further studies. How to cite this article: Gulati S, Chunduru K, Madiyal M, Setia MS, Saravu K. Validation of a Clinical Risk-scoring Algorithm for Scrub Typhus Severity in South India. Indian J Crit Care Med 2021;25(5):551-556.
Language	English
Publishing date	2021-06-10
Publishing country	India
Document type	Journal Article
ZDB-ID	2121263-6
ISSN	1998-359X ; 0972-5229
ISSN (online)	1998-359X
ISSN	0972-5229
DOI	10.5005/jp-journals-10071-23828
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Article ; Online: In silico Study to Evaluate the Antiviral Activity of Novel Structures against 3C-like Protease of Novel Coronavirus (COVID-19) and SARS-CoV.

Chunduru, Kiran / Sankhe, Runali / Begum, Farmiza / Sodum, Nalini / Kumar, Nitesh / Kishore, Anoop / Shenoy, Rekha R / Rao, Chamallamudi M / Saravu, Kavitha

Medicinal chemistry (Shariqah (United Arab Emirates))

2020 Volume 17, Issue 4, Page(s) 380–395

Abstract: Background: Globally, over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative chemistry ... ...

Abstract	Background: Globally, over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative chemistry pipeline, have generated structures that can be potential novel drug-like inhibitors for COVID-19, provided they are validated. 3C-like protease (3CLP) is a homodimeric cysteine protease that is present in coronaviruses. Interestingly, 3CLP is 96.1% structurally similar between SARS-CoV and SARS-CoV-2. Objective: To evaluate interaction of generated structures with 3CLP of SARS-CoV (RCSB PDB ID: 4MDS). Methods: Crystal structure of human SARS-CoV with a non-covalent inhibitor with resolution: 1.598 Å was obtained and molecular docking was performed to evaluate the interaction with generated structures. The MM-GBSA and IFD-SP were performed to narrow down to the structures with better binding energy and IFD score. The ADME analysis was performed on top 5 hits and further MD simulation was employed for top 2 hits. Results: In XP docking, IFD-SP and molecular dynamic simulation studies, the top 2 hits 32 and 61 showed interaction with key amino acid residue GLU166. Structure 61, also showed interaction with HIS164. These interactions of generated structure 32 and 61, with GLU166 and HIS164, indicate the binding of the selected drug within the close proximity of 3CLP. In the MD simulation, the protein- ligand complex of 4MDS and structure 61 was found to be more stable for 10ns. Conclusion: These identified structures can be further assessed for their antiviral activity to combat SARS-CoV and COVID-19.
MeSH term(s)	Antiviral Agents/chemistry ; Antiviral Agents/metabolism ; COVID-19/drug therapy ; Catalytic Domain ; Coronavirus 3C Proteases/antagonists & inhibitors ; Coronavirus 3C Proteases/chemistry ; Coronavirus 3C Proteases/metabolism ; Drug Discovery ; Humans ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Protease Inhibitors/chemistry ; Protease Inhibitors/metabolism ; Protein Binding ; Protein Conformation ; Protein Interaction Domains and Motifs ; SARS Virus/chemistry ; SARS Virus/enzymology ; SARS-CoV-2/chemistry ; SARS-CoV-2/enzymology ; Small Molecule Libraries/chemistry ; Small Molecule Libraries/metabolism ; Structural Homology, Protein ; Structure-Activity Relationship ; Substrate Specificity ; Thermodynamics ; User-Computer Interface
Chemical Substances	Antiviral Agents ; Protease Inhibitors ; Small Molecule Libraries ; Coronavirus 3C Proteases (EC 3.4.22.28)
Keywords	covid19
Language	English
Publishing date	2020-07-27
Publishing country	Netherlands
Document type	Journal Article
ISSN	1875-6638
ISSN (online)	1875-6638
DOI	10.2174/1573396316999200727125522
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Unboxing AI - Radiological Insights Into a Deep Neural Network for Lung Nodule Characterization.

Venugopal, Vasantha Kumar / Vaidhya, Kiran / Murugavel, Murali / Chunduru, Abhijith / Mahajan, Vidur / Vaidya, Suthirth / Mahra, Digvijay / Rangasai, Akshay / Mahajan, Harsh

Academic radiology

2019 Volume 27, Issue 1, Page(s) 88–95

Abstract: Rationale and objectives: To explain predictions of a deep residual convolutional network for characterization of lung nodule by analyzing heat maps.: Materials and methods: A 20-layer deep residual CNN was trained on 1245 Chest CTs from National ... ...

Abstract	Rationale and objectives: To explain predictions of a deep residual convolutional network for characterization of lung nodule by analyzing heat maps. Materials and methods: A 20-layer deep residual CNN was trained on 1245 Chest CTs from National Lung Screening Trial (NLST) trial to predict the malignancy risk of a nodule. We used occlusion to systematically block regions of a nodule and map drops in malignancy risk score to generate clinical attribution heatmaps on 103 nodules from Lung Image Database Consortium image collection and Image Database Resource Initiative (LIDC-IDRI) dataset, which were analyzed by a thoracic radiologist. The features were described as heat inside nodule -bright areas inside nodule, peripheral heat continuous/interrupted bright areas along nodule contours, heat in adjacent plane -brightness in scan planes juxtaposed with the nodule, satellite heat - a smaller bright spot in proximity to nodule in the same scan plane, heat map larger than nodule bright areas corresponding to the shape of the nodule seen outside the nodule margins and heat in calcification. Results: These six features were assigned binary values. This feature vector was fedinto a standard J48 decision tree with 10-fold cross-validation, which gave an 85 % weighted classification accuracy with a 77.8% True Positive (TP) rate, 8% False Positive (FP) rate for benign cases and 91.8% TP and 22.2% FP rates for malignant cases. Heat Inside nodule was more frequently observed in nodules classified as malignant whereas peripheral heat, heat in adjacent plane, and satellite heat were more commonly seen in nodules classified as benign. Conclusion: We discuss the potential ability of a radiologist to visually parse the deep learning algorithm generated "heat map" to identify features aiding classification.
MeSH term(s)	Humans ; Lung/diagnostic imaging ; Lung Neoplasms/diagnostic imaging ; Neural Networks, Computer ; Radiographic Image Interpretation, Computer-Assisted ; Solitary Pulmonary Nodule/diagnostic imaging ; Tomography, X-Ray Computed
Language	English
Publishing date	2019-10-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	1355509-1
ISSN	1878-4046 ; 1076-6332
ISSN (online)	1878-4046
ISSN	1076-6332
DOI	10.1016/j.acra.2019.09.015
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Article ; Online: In silico study to evaluate the antiviral activity of novel structures against 3C-like protease of Novel Coronavirus (COVID-19) and SARS-CoV

Chunduru, Kiran / Sankhe, Runali / Begum, Farmiza / Sodum, Nalini / Kumar, Nitesh / Kishore, Anoop / Shenoy, Rekha R. / Rao, C. Mallikarjuna / Saravu, Kavitha

Medicinal Chemistry

2020 Volume 16

Abstract: Background: Globally over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved vaccine or antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative ... ...

Abstract	Background: Globally over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved vaccine or antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative chemistry pipeline have generated structures that can be potential novel drug-like inhibitors for COVID-19, provided they are validated. 3C–like protease (3CLP) is a homodimeric cysteine protease that is present in coronaviruses. Interestingly, 3CLP is 96.1% structurally similar between SARS-CoV and SARS-CoV-2. Objective: To evaluate interaction of generated structures with 3CLP of SARS-CoV (RCSB PDB ID: 4MDS). Method: Crystal structure of human SARS-CoV with a non-covalent inhibitor with resolution: 1.598 Å was obtained and molecular docking was performed to evaluate the interaction with generated structures. The MM-GBSA and IFD-SP were performed to narrow down to the structures with better binding energy and IFD score. The ADME analysis was performed on top 5 hits and further MD simulation was employed for top 2 hits. Results: In XP docking, IFD-SP and molecular dynamic simulation studies, the top 2 hits 32 and 61 showed interaction with key amino acid residue GLU166. The structure 61, also showed interaction with HIS164. These interactions of generated structure 32 and 61, with GLU166 and HIS164 indicates the binding of selected drug within the close proximity of 3CLP. In the MD simulation the protein–ligand complex of 61 and 4MDS was found to be more stable for 10ns. Conclusion: These identified structures can be further assessed for their antiviral activity to combat SARS-CoV and COVID-19.
Keywords	Drug Discovery ; covid19
Language	English
Publisher	Bentham Science Publishers Ltd.
Publishing country	nl
Document type	Article ; Online
ISSN	1573-4064
DOI	10.2174/1573396316999200727125522
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: In silico study to evaluate the antiviral activity of novel structures against 3C-like protease of Novel Coronavirus (COVID-19) and SARS-CoV

Chunduru, Kiran / Sankhe, Runali / Begum, Farmiza / Sodum, Nalini / Kumar, Nitesh / Kishore, Anoop / Shenoy, Rekha R / Rao, C Mallikarjuna / Saravu, Kavitha

Medicinal chemistry (Hilversum. Online)

Abstract: BACKGROUND: Globally over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved vaccine or antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative ... ...

Abstract	BACKGROUND: Globally over 4.3 million laboratory confirmed cases of COVID-19 have been reported from over 105 countries. No FDA approved vaccine or antiviral is available for the treatment of this infection. Zhavoronkov et al., with their generative chemistry pipeline have generated structures that can be potential novel drug-like inhibitors for COVID-19, provided they are validated. 3C-like protease (3CLP) is a homodimeric cysteine protease that is present in coronaviruses. Interestingly, 3CLP is 96.1% structurally similar between SARS-CoV and SARS-CoV-2. OBJECTIVE: To evaluate interaction of generated structures with 3CLP of SARS-CoV (RCSB PDB ID: 4MDS). METHOD: Crystal structure of human SARS-CoV with a non-covalent inhibitor with resolution: 1.598 Å was obtained and molecular docking was performed to evaluate the interaction with generated structures. The MM-GBSA and IFD-SP were performed to narrow down to the structures with better binding energy and IFD score. The ADME analysis was performed on top 5 hits and further MD simulation was employed for top 2 hits. RESULTS: In XP docking, IFD-SP and molecular dynamic simulation studies, the top 2 hits 32 and 61 showed interaction with key amino acid residue GLU166. The structure 61, also showed interaction with HIS164. These interactions of generated structure 32 and 61, with GLU166 and HIS164 indicates the binding of selected drug within the close proximity of 3CLP. In the MD simulation the protein-ligand complex of 61 and 4MDS was found to be more stable for 10ns. CONCLUSION: These identified structures can be further assessed for their antiviral activity to combat SARS-CoV and COVID-19.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #688767
Database	COVID19

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Article ; Online: LNDb challenge on automatic lung cancer patient management.

Pedrosa, João / Aresta, Guilherme / Ferreira, Carlos / Atwal, Gurraj / Phoulady, Hady Ahmady / Chen, Xiaoyu / Chen, Rongzhen / Li, Jiaoliang / Wang, Liansheng / Galdran, Adrian / Bouchachia, Hamid / Kaluva, Krishna Chaitanya / Vaidhya, Kiran / Chunduru, Abhijith / Tarai, Sambit / Nadimpalli, Sai Prasad Pranav / Vaidya, Suthirth / Kim, Ildoo / Rassadin, Alexandr /

Tian, Zhenhuan / Sun, Zhongwei / Jia, Yizhuan / Men, Xuejun / Ramos, Isabel / Cunha, António / Campilho, Aurélio

Medical image analysis

2021 Volume 70, Page(s) 102027

Abstract: Lung cancer is the deadliest type of cancer worldwide and late detection is the major factor for the low survival rate of patients. Low dose computed tomography has been suggested as a potential screening tool but manual screening is costly and time- ... ...

Abstract	Lung cancer is the deadliest type of cancer worldwide and late detection is the major factor for the low survival rate of patients. Low dose computed tomography has been suggested as a potential screening tool but manual screening is costly and time-consuming. This has fuelled the development of automatic methods for the detection, segmentation and characterisation of pulmonary nodules. In spite of promising results, the application of automatic methods to clinical routine is not straightforward and only a limited number of studies have addressed the problem in a holistic way. With the goal of advancing the state of the art, the Lung Nodule Database (LNDb) Challenge on automatic lung cancer patient management was organized. The LNDb Challenge addressed lung nodule detection, segmentation and characterization as well as prediction of patient follow-up according to the 2017 Fleischner society pulmonary nodule guidelines. 294 CT scans were thus collected retrospectively at the Centro Hospitalar e Universitrio de So Joo in Porto, Portugal and each CT was annotated by at least one radiologist. Annotations comprised nodule centroids, segmentations and subjective characterization. 58 CTs and the corresponding annotations were withheld as a separate test set. A total of 947 users registered for the challenge and 11 successful submissions for at least one of the sub-challenges were received. For patient follow-up prediction, a maximum quadratic weighted Cohen's kappa of 0.580 was obtained. In terms of nodule detection, a sensitivity below 0.4 (and 0.7) at 1 false positive per scan was obtained for nodules identified by at least one (and two) radiologist(s). For nodule segmentation, a maximum Jaccard score of 0.567 was obtained, surpassing the interobserver variability. In terms of nodule texture characterization, a maximum quadratic weighted Cohen's kappa of 0.733 was obtained, with part solid nodules being particularly challenging to classify correctly. Detailed analysis of the proposed methods and the differences in performance allow to identify the major challenges remaining and future directions - data collection, augmentation/generation and evaluation of under-represented classes, the incorporation of scan-level information for better decision-making and the development of tools and challenges with clinical-oriented goals. The LNDb Challenge and associated data remain publicly available so that future methods can be tested and benchmarked, promoting the development of new algorithms in lung cancer medical image analysis and patient follow-up recommendation.
MeSH term(s)	Algorithms ; Databases, Factual ; Humans ; Lung Neoplasms/diagnostic imaging ; Retrospective Studies ; Solitary Pulmonary Nodule ; Tomography, X-Ray Computed
Language	English
Publishing date	2021-03-05
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1356436-5
ISSN	1361-8423 ; 1361-8431 ; 1361-8415
ISSN (online)	1361-8423 ; 1361-8431
ISSN	1361-8415
DOI	10.1016/j.media.2021.102027
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