TYPE,NAME,INFOHASH,SIZEBYTES,MIRRORS,DOWNLOADERS,TIMESCOMPLETED,DATEADDED,DATEMODIFIED
Dataset,"OpenMIIR RawEEG v1.0",c18c04a9f18ff7d133421012978c4a92f57f6b9c,6995284395,12,0,888,1434467329,1599249433
Dataset,"Scendesmus dataset",338a9fb90e5dccda4106d623768b6d40f3956ab0,589623527,6,0,69,1473643095,1599249386
Dataset,"Water microdroplet dataset",a8d14f22c9ce1cc59c9f480df5deb0f7e94861f4,95152553,7,0,221,1473643729,1599249506
Dataset,"Gland Segmentation in Histology Images Challenge (GlaS) Dataset",208814dd113c2b0a242e74e832ccac28fcff74e5,180902609,9,0,531,1474493147,1599249431
Dataset,"Open Payments Dataset - 2013 Program Year",92a1aeaaf741f3d1669ad0f0186d96ec168ee550,277982372,8,0,118,1488126519,1599249654
Dataset,"Open Payments Dataset - 2014 Program Year",88f6fff84d7c2a2769348ab4c2b0ecb318b43752,728444845,7,0,243,1488127301,1599249514
Dataset,"VGG Cell Dataset from Learning To Count Objects in Images",b32305598175bb8e03c5f350e962d772a910641c,16339802,8,0,285,1491094963,1599249373
Dataset,"Human acute monocytic leukemia",8464b9f9166c143040fee655f0284085fe251a80,1609437908,7,0,145,1493422482,1599249263
Dataset,"NIH Pancreas-CT Dataset",80ecfefcabede760cdbdf63e38986501f7becd49,4863883044,24,0,17557,1505241389,1599249505
Dataset,"Ischemic Stroke Lesion Segmentation Challenge 2017 (ISLES2017)",5bdb401695ad36d4ccd73da90c2f9f8ab6f82092,1403654243,11,0,1189,1505317133,1599249408
Dataset,"Non-Small Cell Lung Cancer CT Scan Dataset (NSCLC-Radiomics-Genomics)",95b58ebfc1952780cfe2102dd7290889feefad66,4522256159,12,0,515,1505841529,1599249224
Dataset,"MICCAI 2015 Challenge on Multimodal Brain Tumor Segmentation (BraTS2015)",c4f39a0a8e46e8d2174b8a8a81b9887150f44d50,5340438240,9,0,686,1505842084,1599249233
Dataset,"NIH Chest X-ray Dataset of 14 Common Thorax Disease Categories",557481faacd824c83fbf57dcf7b6da9383b3235a,45089461497,16,0,4585,1507562340,1599249439
Dataset,"Electron Microscopy (CA1 hippocampus) Dataset",3ada3ae6ec71097e63d897cf878051bba3eaba25,3873351785,11,0,214,1508839502,1599249629
Dataset,"Breast Cancer Cell Segmentation",b79869ca12787166de88311ca1f28e3ebec12dec,159955958,9,0,1470,1519069114,1599249262
Dataset,"Malignant lymphoma classification",3cde17e7e4d9886513630c1005ba20b8d37c333a,1441583313,13,0,6746,1519070265,1599249392
Dataset,"Caudate Segmentation Evaluation 2007 (CAUSE07)",d6c066ef308cc704c8898d5f87cf55e986475fb5,1887197764,7,0,85,1520462031,1599249656
Dataset,"MICCAI 2013 Challenge on Multimodal Brain Tumor Segmentation (BraTS2013)",39c5a52bda7b5b701cecfc454a79d385868d4f3d,19706785133,8,0,628,1520557523,1599249516
Dataset,"MRI Lesion Segmentation in Multiple Sclerosis Database",e08155e5022d688fea00319bd2ead4f0f703f5bb,193085367,12,0,971,1523223569,1599249512
Dataset,"Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Image Data",d01d7568512efe5a9ad0525af853cab9ff921e51,2640815762,8,0,123,1523292062,1599249509
Dataset,"A collection of sport activity datasets with an emphasis on powermeter data",bf76b193960a96a683f9c2afde70acab9d3d757d,919751720,13,1,2050,1529744925,1599249639
Dataset,"LUng Nodule Analysis (LUNA16) All Images",58b053204337ca75f7c2e699082baeb57aa08578,65995402313,11,0,3229,1531673350,1599249506
Dataset,"LiTS – Liver Tumor Segmentation Challenge (LiTS17)",27772adef6f563a1ecc0ae19a528b956e6c803ce,16655115138,18,0,10148,1532208088,1599672269
Dataset,"Human MCF7 cells – compound-profiling experiment (BBBC021v1)",014980e8a505760ed4c33641ac7e603d6e1778f4,45688728298,7,0,62,1534736167,1599249522
Dataset,"MoNuSeg Training Data - Multi-organ nuclei segmentation from H&E stained histopathological images",c87688437fb416f66eecbd8c419aba00dd12997f,142306116,8,0,191,1536186326,1599249653
Dataset,"Medical Segmentation Decathlon Datasets",274be65156ed14828fb7b30b82407a2417e1924a,75906970628,8,0,270,1537440844,1599249660
Dataset,"MICCAI_BraTS_2018_Data_Training",a9e2741587d42ef6139aa474a95858a17952b3a5,2325982089,6,0,1195,1538752029,1599249574
Dataset,"MICCAI_BraTS_2018_Data_Validation",a5912da845c7d7bec9bd0880c17ddda789ba35d5,671065146,6,0,827,1538752104,1599249653
Dataset,"Non-contrast head/brain CT CQ500 Dataset",47e9d8aab761e75fd0a81982fa62bddf3a173831,28660285880,11,1,7178,1538754509,1662662330
Dataset,"BRATS2013 Tumor-NoTumor Dataset (T-NT)",d52ccc21455c7a82fd6e58964c89b7da99e0edf7,65630646,8,0,1992,1541393360,1599249382
Dataset,"The PatchCamelyon benchmark dataset (PCAM)",1561a180b11d4b746273b5ce46772ad36f1229b6,8061211742,7,0,110,1542118185,1599249439
Dataset,"Zinc Molecule Dataset from Constrained Graph Variational Autoencoders for Molecule Design",4776b264ca3c4ed05530124b6319ce0d45aff626,33939265,5,0,107,1542373795,1599249660
Dataset,"Indiana University - Chest X-Rays (XML Reports)",66450ba52ba3f83fbf82ef9c91f2bde0e845aba9,1112632,28,0,26634,1542900896,1599249262
Dataset,"Indiana University - Chest X-Rays (PNG Images)",5a3a439df24931f410fac269b87b050203d9467d,1360814128,33,0,24216,1542902411,1599249484
Dataset,"Chest X-Ray Images (Pediatric Pneumonia)",7208a86910cc518ae8feaa9021bf7f8565b97644,1236184657,8,0,3439,1544813267,1608582614
Dataset,"Labeled Optical Coherence Tomography (OCT)",198145c88af9a1d61ba8070f5b05c3539896ff4e,5793183169,9,0,131,1544896873,1599249653
Dataset,"genemania.pkl",5adbacb0b7ea663ac4a7758d39250a1bd28c5b40,9614641,7,0,78,1547250710,1599249519
Dataset,"regnet.pkl",e109e087a8fc8aec45bae3a74a193922ce27fc58,8809906,7,0,85,1547251122,1599249614
Dataset,"DeepLesion (10,594 CT scans with lesions)",de50f4d4aa3d028944647a56199c07f5fa6030ff,243037288033,11,4,2043,1548522158,1599249611
Dataset,"Kaggle Diabetic Retinopathy Detection Training Dataset (DRD)",08c244595c6cc4ec403b21023cf99c2b085cbc72,34999421799,8,0,2348,1549431917,1599249546
Dataset,"IDRiD (Indian Diabetic Retinopathy Image Dataset)",3bb974ffdad31f9df9d26a63ed2aea2f1d789405,1010096056,12,0,15693,1549438671,1599249494
Dataset,"Montgomery County X-ray Set",ac786f74878a5775c81d490b23842fd4736bfe33,616853875,24,1,27477,1549900562,1599249644
Dataset,"Shenzhen Hospital X-ray Set",462728e890bd37c05e9439c885df7afc36209cc8,3770205534,8,0,1148,1549901169,1599249547
Dataset,"Invasive Ductal Carcinoma (IDC) Histology Image Dataset",e40bd59ab08861329ce3c418be191651f35e2ffa,1644892042,10,0,1542,1550877244,1599249547
Dataset,"Lung CT Segmentation Challenge 2017 (LCTSC)",0a3611528c9172383656cb1b6a07cfb7f095eb82,5108773000,8,0,1063,1553268148,1599249635
Dataset,"PADCHEST_SJ (Feb 2019 Update)",dec12db21d57e158f78621f06dcbe78248d14850,1127527483252,6,1,124,1554602843,1599249622
Dataset,"Head-Neck-CT",d06aafd957f0c8c9b0eb4636e5c3ebdb7bdaf54f,22836341441,8,0,273,1555876335,1599249545
Dataset,"PROSTATEx",5a447ff50062194bd58dd11c0fedead59e6d873c,4324268308,7,0,622,1556387716,1599249654
Dataset,"1000 Genomes Project",648ded078fbdfec60ce1c30e7f699624f6b05c7a,17416339333,8,0,160,1559063680,1599249201
Dataset,"MIT-BIH Arrhythmia Database",78d14c9cb4fa765b3c323c1a26bd114e2b30ef34,93861490,9,0,265,1559159458,1599249668
Dataset,"DiaRetDB1 V2.1 - Diabetic Retinopathy Database",817b91fd639263f6f644de4ccc9575c20b005c6c,144096332,12,0,6691,1559702718,1599249659
Dataset,"DRIMDB (Diabetic Retinopathy Images Database) Database for Quality Testing of Retinal Images",99811ba62918f8e73791d21be29dcc372d660305,17074713,9,0,5316,1559703679,1599249177
Dataset,"2D ultrasound sequences of the liver (mp4)",4d107e9fd4b00fa797504d6cd0131744c9f31e81,107394613,9,0,483,1560635712,1599249336
Dataset,"ISIC2018: Skin Lesion Analysis Towards Melanoma Detection",1e3811b66f1129a2b86b7c291316db8583dbc94f,17082696680,7,0,467,1563983307,1599249655
Dataset,"ISIC2017: Skin Lesion Analysis Towards Melanoma Detection",152479c5e0b31c05c8fafbc23fcd5a20bf7f910b,13006801360,14,0,4085,1563985462,1599249633
Dataset,"Images of thin blood smears with bounding boxes around malaria parasites (malaria-655)",baa7ef7e09a123c04c516d7226193423f4f2e5b3,105447054,8,0,828,1564711830,1599249171
Dataset,"P. vivax (malaria) infected human blood smears (BBBC041)",2fed90eeaa0fbf98aba474c5d7e56f6290121507,2259224287,8,0,288,1564717065,1599249390
Dataset,"RIGA dataset (Retinal fundus images for glaucoma analysis)",eb9dd9216a1c9a622250ad70a400204e7531196d,13840106500,7,0,348,1565230979,1599249213
Dataset,"Longitudinal diabetic retinopathy screening data",744717095e59373186abec814c86de4831d889e9,4857449318,7,0,1567,1565985187,1599249394
Dataset,"MRI Dataset for Hippocampus Segmentation (HFH) (hippseg_2011)",d019f4f082f3fda94f0f74577b50dc30beee7bf8,598881636,7,0,731,1566309314,1599249636
Dataset,"1000 Fundus images with 39 categories",6d239d7d6c23f8b2a8046cca7078a7e10c6889d0,402759715,8,0,1118,1566312641,1599249667
Dataset,"L1000 Connectivity Map perturbational profiles from Broad Institute LINCS Center for Transcriptomics LINCS PHASE *II* (n=354,123; updated March 30, 2017) (Level 5 data)",99970027a2a6bd6eceb8b9113346f899a50e17be,5365179698,6,0,41,1573597113,1599249385
Dataset,"Ocular Disease Intelligent Recognition ODIR-5K",cf3b8d5ecdd4284eb9b3a80fcfe9b1d621548f72,1300482376,14,0,7668,1574709667,1599249173
Dataset,"NIH Chest X-ray Dataset (Resized to 224x224)",e615d3aebce373f1dc8bd9d11064da55bdadede0,2513363817,19,0,7051,1575154252,1599249642
Dataset,"LNDb CT scan dataset (training)",e3c196b07c8ea94ac5fca872bccf2cc035f4e88d,29209516876,8,0,242,1576518921,1599249658
Dataset,"LC25000 Lung and colon histopathological image dataset",7a638ed187a6180fd6e464b3666a6ea0499af4af,1890299770,52,0,51355,1578281464,1599672383
Dataset,"Pediatric Chest X-ray Pneumonia (Bacterial vs Viral vs Normal) Dataset",951f829a8eeb4d2839c4a535db95078a9175010b,1236482806,10,1,707,1583623627,1599249563
Dataset,"RSNA Pneumonia Detection Challenge (DICOM files)",a0d80e1bb03ef8357d71e058ef9471b4468cd18e,3956488926,10,0,519,1584592336,1599249202
Dataset,"RSNA Pneumonia Detection Challenge (JPG files)",95588a735c9ae4d123f3ca408e56570409bcf2a9,3928285701,11,0,1337,1584592477,1621614861
Dataset,"MICCAI_BraTS_2019_Data_Training",82cef583fa17480b0f9a6342591d01dc67abe055,2759083974,8,0,1231,1590000379,1599247791
Dataset,"PMC Open Access Subset",06d6badd7d1b0cfee00081c28fddd5e15e106165,84144856912,8,0,221,1590288023,1599249672
Dataset,"SIIM-ACR Pneumothorax Segmentation",6ef7c6d039e85152c4d0f31d83fa70edc4aba088,2072340626,8,0,802,1593828455,1666141512
Dataset,"Object-CXR - Automatic detection of foreign objects on chest X-rays",fdc91f11d7010f7259a05403fc9d00079a09f5d5,13636253487,8,0,1295,1594238373,1652304529
Dataset,"DRIVE: Digital Retinal Images for Vessel Extraction",062dc18f55b086c76c718ac88f98972789b3c04c,29343870,15,0,20214,1594504912,1599249170
Dataset,"PanNuke: An Open Pan-Cancer Histology Dataset for Nuclei Instance Segmentation and Classification",99f2c7b57b95500711e33f2ee4d14c9fd7c7366c,2077087715,10,0,460,1597377637,1599249617
Dataset,"TB Portal Tuberculosis Chest X-ray dataset for Belarus",509f986b456b6fce04c15f9d1de22cd4ccb2c4b7,12398871154,8,0,394,1603339369,1606928930
Dataset,"Breast Ultrasound Images Dataset (Dataset BUSI)",d0b7b7ae40610bbeaea385aeb51658f527c86a16,205873341,12,0,4900,1614983926,1673902907
Dataset,"TotalSegmentator CT Dataset",337819f0e83a1c1ac1b7262385609dad5d485abf,28404091806,9,0,132,1668702250,1702320852
Dataset,"Data of the White Matter Hyperintensity (WMH) Segmentation Challenge",a6d90ae5a9ff4cc8184f122048495fd6bd18d6ba,8715128611,9,0,66,1671649290,1671651576
Dataset,"STructured Analysis of the Retina",e4554cd63400dc13b74477efe98032c10757c269,484369267,8,0,897,1672519413,1674332133
Dataset,"HMC-QU echocardiography ultrasound recordings",11832dbd0b58c1dd9305a10373c9536872dd31af,2492458234,12,0,935,1673108668,1673109574
Dataset,"CAMUS Cardiac Acquisitions for Multi-structure Ultrasound Segmentation",ae545c1e3ce045c33942f89e67f618a6439104a6,3833291884,12,0,519,1673564487,1673565157
Dataset,"SegThy Open-Access Dataset for Thyroid and Neck Segmentation",a6530eb901e8c1c127166d1bebeffb0129f5bf9f,18577127500,7,0,37,1673909900,1700160080
Dataset,"TotalSegmentator CT Dataset V2",1dfeb3186514b40a2c212c21d494c665766bfbf4,23586975073,8,0,57,1696392734,1698878989
Dataset,"Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation",8277ce3d862883f08846d87099e3af4d89fd94c1,24234336519,10,0,93,1696488043,1703094801
Dataset,"VerSe'20 CT Dataset",0ac07fd4ddf1802208f88c61c5ccf7d029d87a18,38678870472,6,0,36,1703104997,1703108491
Dataset,"DENTEX_CHALLENGE",6b44adbe4c64591e859b57ffe04c091cf6cfd946,10927391529,7,0,23,1703439091,1703439835