Johannes Zimmermann, Christoph Kaleta, Silvio Waschina
Genome biology·
2021·
cited by 311
Automated reconstruction of microbial metabolic models often fails to recapitulate known metabolic processes, limiting phenotype prediction from genomes.
Tommaso Biancalani, Gabriele Scalia, Lorenzo Buffoni, Raghav Avasthi, Ziqing Lu, Aman Sanger, Neriman Tokcan, Charles R. Vanderburg et al.
Nature Methods·
2021·
cited by 915
Single-cell RNA-seq loses spatial information while spatial technologies have limited resolution, sensitivity, or gene throughput, blocking full organ atlases.
Edgar Omar Molina-Molina, Selene Solorza-Calderón, Josué Álvarez-Borrego
Applied Sciences·
2020·
cited by 36
Medicine & Health
Cutaneous Melanoma Detection and Management
ai assisted
importance 7/10
scale stated
Detecting skin diseases and skin cancer from dermoscopy color images to aid dermatologists in diagnosis.
Tomasz Lewick, Meera Kumar, Raymond Hong, Wencen Wu
IEEE International Conference on Big Data Computing Service and Applications (BigDataService)·
2020·
cited by 36
Medicine & Health
Intracerebral and Subarachnoid Hemorrhage Research
ai assisted
importance 7/10
scale stated
Patient mortality in intracranial hemorrhage depends on prompt diagnosis from radiologist assessment of CT scans; a deep learning model was built to accelerate identification.
Gabriele Franch, Daniele Nerini, Marta Pendesini, Luca Coviello, Giuseppe Jurman, Cesare Furlanello
Atmosphere·
2020·
cited by 97
Deep learning precipitation nowcasting models underperform on extreme rainfall rates due to prediction smoothing, weakening short-term flash-flood and thunderstorm forecasts.
Ji Young Lee, Jong Soo Kim, Tae Yoon Kim, Young Soo Kim
Scientific Reports·
2020·
cited by 119
Medicine & Health
Intracerebral and Subarachnoid Hemorrhage Research
ai assisted
importance 7/10
scale stated
Detecting intracranial haemorrhage and classifying its subtypes on CT images is difficult and needs accurate automated methods.
Joseph Thaddeus Beck, Melissa Rammage, Gretchen Purcell Jackson, Anita M. Preininger, Irene Dankwa‐Mullan, M. Christopher Roebuck, Adam Torres, Helen Holtzen et al.
JCO Clinical Cancer Informatics·
2020·
cited by 127
Medicine & Health
Artificial Intelligence in Healthcare and Education
partially solved
importance 7/10
scale stated
Fewer than 5% of cancer patients enroll in clinical trials and 1 in 5 trials stop for poor accrual, partly because manual eligibility screening from unstructured records is slow.
Brian Hie, Bryan D. Bryson, Bonnie Berger
Cell Systems·
2020·
cited by 153
Machine learning models fail when predicting beyond their training distribution, hindering biological discovery such as finding active compounds from very small datasets.
Zhang Li, Jiehua Zhang, Tao Tan, Xichao Teng, Xiaoliang Sun, Hong Zhao, Lihong Liu, Yang Xiao et al.
IEEE Journal of Biomedical and Health Informatics·
2020·
cited by 157
Medicine & Health
AI in cancer detection
partially solved
importance 7/10
scale stated
Automatically segmenting lung cancer tissue pixel-wise in whole-slide histopathology images to support diagnosis.
Yongjia Song, Yuhang Wang
Remote Sensing·
2020·
cited by 28
Predicting monthly wildfire burned area up to one year in advance across major global fire regions to support planning and preparedness.
Riku Turkki, Dmitrii Bychkov, Mikael Lundin, Jorma J Isola, Stig Nordling, Panu E. Kovanen, Clare L. Verrill, Karl von Smitten et al.
Breast Cancer Research and Treatment·
2019·
cited by 130
Predicting breast cancer patient outcomes from tumour tissue images alone, rather than relying solely on human expert assessment.
Daniel Shu Wei Ting, Carol Yim-lui Cheung, Gilbert Lim, Gavin Siew Wei Tan, Duc Quang Nguyen, Alfred Tau Liang Gan, Haslina Hamzah, Renata García-Franco et al.
JAMA·
2017·
cited by 2,383
Detecting referable and vision-threatening diabetic retinopathy, possible glaucoma, and age-related macular degeneration from retinal images in multiethnic populations with diabetes.
Giuseppe Carleo, Matthias Troyer
Science·
2017·
cited by 2,205
The exponential complexity of the many-body wave function makes describing interacting quantum systems computationally intractable.
Michael P. Menden, Francesco Iorio, Mathew J. Garnett, Ultan McDermott, Cyril H. Benes, Pedro J. Ballester, Julio Sáez-Rodríguez
PLoS ONE·
2013·
cited by 543
Medicine & Health
Computational Drug Discovery Methods
partially solved
importance 7/10
scale stated
Predicting how sensitive specific cancer cell lines are to drug treatment, a step toward personalised cancer therapy.
Ousman Khan, Jimoh Olawale Ajadi, M. Pear Hossain
PLoS ONE·
2024·
cited by 36
Medicine & Health
Malaria Research and Control
partially solved
importance 7/10
scale stated
Malaria outbreaks in the districts of The Gambia are hard to anticipate, posing a growing threat to public health and economic growth.
Philipp Rentzsch, Max Schubach, Jay Shendure, Martin Kircher
Genome Medicine·
2021·
cited by 637
Medicine & Health
Genomics and Rare Diseases
partially solved
importance 7/10
scale stated
Genetic variants affecting splicing are hard to identify beyond donor/acceptor dinucleotides, underpinning much genetic disease.
Ángel Cruz-Roa, Hannah L. Gilmore, Ajay N. Basavanhally, Michael D. Feldman, Shridar Ganesan, Natalie N. C. Shih, John Tomaszewski, Fabio Augusto Gonzalez et al.
Scientific Reports·
2017·
cited by 532
Manually identifying the presence and extent of invasive breast cancer in whole-slide pathology images is tedious and subject to inter- and intra-reader variability.
Ting Zhang, Ran Zhang, Jianzhu Li, Ping Feng
Hydrology and earth system sciences·
2025·
cited by 16
Deep learning flood forecasting models often lack interpretability and physical realism, limiting trust in predictions.
Suhaas Bhat, Kalyan Palepu, Lauren Hong, Yiwei Mao, Tianzheng Ye, Rema Iyer, Lin Zhao, Tianlai Chen et al.
Science Advances·
2025·
cited by 64
Medicine & Health
Chemical Synthesis and Analysis
partially solved
importance 7/10
scale stated
Designing molecules that bind to 'undruggable' disease proteins is a major challenge in drug discovery. PepPrCLIP was created to design short target-binding peptides using only the target protein's amino acid sequence.
Zia-ur-Rehman, Mohd Khalid Awang, Javed Rashid, Ghulam Ali, Muhammad Hamid, Samy Farouk Mahmoud, Dalia I. Saleh, Hafiz Ishfaq Ahmad
PLoS ONE·
2024·
cited by 30
Medicine & Health
Dementia and Cognitive Impairment Research
ai assisted
importance 7/10
scale stated
Alzheimer's disease has no cure, so detecting it early from MRI scans and distinguishing its stages is critical but difficult.
Maurizio Titz, Franz J. Kaiser, Johannes Kruse, Dirk Witthaut
Chaos An Interdisciplinary Journal of Nonlinear Science·
2024·
cited by 15
Predicting the risk of power grid desynchronization after transmission line failures, a major threat to grid stability.
Cyril Zakka, Rohan Shad, Akash R. Chaurasia, Alex R. Dalal, Jennifer L. Kim, Michael Moor, Robyn Fong, Curran Phillips et al.
NEJM AI·
2024·
cited by 401
Medicine & Health
Artificial Intelligence in Healthcare and Education
partially solved
importance 7/10
scale stated
Large language models tend to generate incorrect or harmful statements, limiting their adoption for clinical medical guideline and treatment recommendations.
Trieu H. Trinh, Yuhuai Wu, Quoc Viet Le, He He, Thang Luong
Nature·
2024·
cited by 307
Mathematics
AI-based Problem Solving and Planning
solved
importance 7/10
scale stated
Automated proving of olympiad-level geometry theorems was blocked by the scarcity of human demonstrations in machine-verifiable format.
Feng Ren, Alex Aliper, Jian Chen, Heng Zhao, Sujata Rao, Christoph Kuppe, Ivan V. Ozerov, Man Zhang et al.
Nature Biotechnology·
2024·
cited by 330
Medicine & Health
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
partially solved
importance 7/10
scale stated
Idiopathic pulmonary fibrosis is an aggressive, high-mortality lung disease where putative drug targets have failed to translate into effective clinical therapies.