Liu Yang

All Publications

• Advancements in Fetal Heart Rate Monitoring: A Report on Opportunities and Strategic Initiatives for Better Intrapartum Care. BJOG : an international journal of obstetrics and gynaecology Lovers, A., Daumer, M., Frasch, M. G., Ugwumadu, A., Warrick, P., Vullings, R., Pini, N., Tolladay, J., Petersen, O. B., Lederer, C., Yang, L., Djurić, P. M., Abtahi, F., Holzmann, M., Boudet, S., de l'Aulnoit, A. H., Georgieva, A. 2025; 132 (7): 853-866

  Abstract

  Cardiotocography (CTG), introduced in the 1960s, was initially expected to prevent hypoxia-related deaths and neurological injuries. However, more than five decades later, evidence supporting the evidence of intrapartum CTG in preventing neonatal and long-term childhood morbidity and mortality remains inconclusive. At the same time, shortcomings in CTG interpretation have been recognised as important contributory factors to rising caesarean section rates and missed opportunities for timely interventions. An important limitation is its high false-positive rate and poor specificity, which undermines reliably identifying foetuses at risk of hypoxia-related injuries. These shortcomings are compounded by the technology's significant intra- and interobserver variability, as well as the subjective and complex nature of fetal heart rate interpretation. However, human factors and other environmental factors are equally significant. Advancements in fetal heart rate monitoring are crucial to support clinicians in improving health outcomes for newborns and their mothers, while at the same time avoiding unnecessary operative deliveries. These limitations highlight the clinical need to enhance neonatal outcomes while minimising unnecessary interventions, such as instrumental deliveries or caesarean sections. We believe that achieving this requires a paradigm shift from subjective interpretation of complex and nonspecific fetal heart rate patterns to evidence-based, quantifiable solutions that integrate hardware, engineering and clinical perspectives. Such transformation necessitates an international, multidisciplinary effort encompassing the entire continuum of pregnancy care and the broader healthcare ecosystem, with emphasis on well-defined, actionable health outcomes. Achieving this will depend on collaborations between researchers, clinicians, medical device manufacturers and other relevant stakeholders. This expert review paper outlines the most relevant and promising directions for research and strategic initiatives to address current challenges in fetal heart rate monitoring. Key themes include advancements in computerised fetal heart rate monitoring, the application of big data and artificial intelligence, innovations in home and remote monitoring and consideration of human factors.

  View details for DOI 10.1111/1471-0528.18097

  View details for PubMedID 39971749

  View details for PubMedCentralID PMC12051231

• Digital twins, synthetic patient data, and in-silico trials: can they empower paediatric clinical trials? The Lancet. Digital health Pammi, M., Shah, P. S., Yang, L. K., Hagan, J., Aghaeepour, N., Neu, J. 2025: 100851

  Abstract

  Randomised controlled trials are the gold standard to assess the effectiveness and safety of clinical interventions; however, many paediatric trials are discontinued early due to challenges in patient enrolment. Hence, most paediatric clinical trials suffer from lack of adequate power. Additionally, trials are expensive and might expose patients to unproven therapies. Alternatives to overcome these issues using virtual patient data-namely, digital twins, synthetic patient data, and in-silico trials-are now possible due to rapid advances in digital health-care tools and interventions. However, such digital innovations have been rarely used in paediatric trials. In this Viewpoint, we propose using virtual patient data to empower paediatric trials. The use of virtual patient data has the advantages of decreased exposure of children to potentially ineffective or risky interventions, shorter trial durations leading to more rapid ascertainment of safety and effectiveness of interventions, and faster drug approvals. Use of virtual patient data could lead to more personalised treatment options with low costs and could result in faster clinical implementation of interventions in children. However, ethical and regulatory concerns, including replacing humans with digital data, data privacy, and security should be addressed and the safety and sustainability of digital data innovation ensured before virtual patient data are adopted widely.

  View details for DOI 10.1016/j.landig.2025.01.007

  View details for PubMedID 40360351

• Ventriculomegaly without elevated intracranial pressure? Normal pressure hydrocephalus as a disorder of the cerebral windkessel FRONTIERS IN NEUROLOGY Mani, R., Basem, J., Yang, L., Abdolmaleki, N., Ravishankar, A., Fiore, S., Djuric, P., Egnor, M. 2025; 16: 1591275

  Abstract

  Normal pressure hydrocephalus (NPH) is characterized by ventriculomegaly without elevations in intracranial pressure (ICP). One way of viewing hydrocephalus is as a disorder of the cerebral windkessel. The cerebral windkessel is the system that dampens the arterial blood pressure (ABP) pulse in the cranium, transmitting this pulse from arteries to veins via the cerebrospinal fluid (CSF) path, bypassing the microvasculature to render capillary flow smooth. When the windkessel is physiologically tuned, windkessel effectiveness (W) is given by: W=IE/R, where I represents CSF path inertance (pulse magnitude), E is CSF path elastance, and R is resistance in the CSF path. In NPH, we posit that there is a combination of arteriosclerosis (blunting the CSF pulse in the SAS- lowering I), and age-related softening of brain tissue (decreasing the elastance of subarachnoid CSF pathways- lowering E).To model the windkessel, we utilize a tank circuit with parallel inductance and capacitance to simulate the pulsatile flow of blood and CSF as alternating current (AC), and smooth flow as direct current (DC). We model NPH as a disorder of windkessel impairment by decreasing windkessel inertance (reflecting diminished CSF pulsatility in the SAS from arteriosclerosis) and decreasing intracranial elastance (reflecting age-related brain atrophy). We simulate ventriculomegaly and shunting by lowering the resistance of this circuit.In simulating NPH using this circuit, we found significant elevations in the amplitude and power of AC in the CSF and capillary paths when inertance and elastance were decreased. Conversely, this pulse power decreased with decreased resistance in the CSF path from ventriculomegaly and shunting.Simulations of NPH demonstrated increased amplitude and power of AC in the CSF and capillary paths due to windkessel impairment. We posit that this pulsatility is redistributed from the SAS to the ventricular CSF path, exerting pulsatile stress on the periventricular leg and bladder fibers, which may explain NPH symptomatology. Ventriculomegaly may represent an active adaptation to improve windkessel effectiveness by decreasing CSF path resistance to mitigate decreased CSF path inertance and parenchymal elastance. Shunting provides a low resistance, accessory windkessel to obviate adaptive ventriculomegaly. This has significant implications in understanding this paradoxical condition.

  View details for DOI 10.3389/fneur.2025.1591275

  View details for Web of Science ID 001487671200001

  View details for PubMedID 40376155

  View details for PubMedCentralID PMC12078120

• AI-guided precision parenteral nutrition for neonatal intensive care units. Nature medicine Phongpreecha, T., Ghanem, M., Reiss, J. D., Oskotsky, T., Mataraso, S. J., De Francesco, D., Reincke, S. M., Espinosa, C., Chung, P., Ng, T., Costello, J. M., Sequoia, J. A., Razdan, S., Xie, F., Berson, E., Kim, Y., Seong, D., Szeto, M. Y., Myers, F., Gu, H., Feister, J., Verscaj, C. P., Rose, L. A., Sin, L. W., Oskotsky, B., Roger, J., Shu, C. H., Shome, S., Yang, L. K., Tan, Y., Levitte, S., Wong, R. J., Gaudillière, B., Angst, M. S., Montine, T. J., Kerner, J. A., Keller, R. L., Shaw, G. M., Sylvester, K. G., Fuerch, J., Chock, V., Gaskari, S., Stevenson, D. K., Sirota, M., Prince, L. S., Aghaeepour, N. 2025

  Abstract

  One in ten neonates are admitted to neonatal intensive care units, highlighting the need for precise interventions. However, the application of artificial intelligence (AI) in guiding neonatal care remains underexplored. Total parenteral nutrition (TPN) is a life-saving treatment for preterm neonates; however, implementation of the therapy in its current form is subjective, error-prone and resource-consuming. Here, we developed TPN2.0-a data-driven approach that optimizes and standardizes TPN using information collected routinely in electronic health records. We assembled a decade of TPN compositions (79,790 orders; 5,913 patients) at Stanford to train TPN2.0. In addition to internal validation, we also validated our model in an external cohort (63,273 orders; 3,417 patients) from a second hospital. Our algorithm identified 15 TPN formulas that can enable a precision-medicine approach (Pearson's R = 0.94 compared to experts), increasing safety and potentially reducing cost. A blinded study (n = 192) revealed that physicians rated TPN2.0 higher than current best practice. In patients with high disagreement between the actual prescriptions and TPN2.0, standard prescriptions were associated with increased morbidities (for example, odds ratio = 3.33; P value = 0.0007 for necrotizing enterocolitis), while TPN2.0 recommendations were linked to reduced risk. Finally, we demonstrated that TPN2.0 employing a transformer architecture enabled guideline-adhering, physician-in-the-loop recommendations that allow collaboration between the care team and AI.

  View details for DOI 10.1038/s41591-025-03601-1

  View details for PubMedID 40133525

  View details for PubMedCentralID 10593864

• Review of theories into the pathogenesis of normal pressure hydrocephalus. BMJ neurology open Mani, R., Basem, J., Yang, L., Fiore, S., Djuric, P., Egnor, M. 2024; 6 (2): e000804

  Abstract

  Normal pressure hydrocephalus (NPH) represents a unique form of hydrocephalus characterised by the paradox of ventriculomegaly without significant elevations in intracranial pressure, with the clinical triad of gait instability, cognitive impairment, and urinary incontinence. A myriad of neurobiological correlates have been implicated in its pathophysiology. We review the literature to provide an up-to-date, narrative review of the proposed mechanisms underlying the pathophysiology of NPH, proposing a holistic framework through which to understand the condition. We conducted a narrative review of the literature on NPH, assessing the various mechanisms underlying its pathophysiology and clinical presentation. NPH represents a unique form of hydrocephalus manifesting as a disorder of the cerebral vasculature, characterised by arteriosclerosis and reduced intracranial elastance. There are multiple mechanisms underlying its pathophysiology, which include windkessel impairment causing redistribution of intracranial pulsatility from the subarachnoid space to the ventricles, reductions in cerebral blood flow, impaired glymphatic clearance, reduced blood-brain barrier integrity and alterations in venous haemodynamics. Moreover, NPH shares similar clinical features and pathological mechanisms as other neurodegenerative conditions such as Alzheimer's disease and vascular dementia. The severity of each respective mechanism of pathophysiology can lead a patient to develop one condition versus another. Analysing NPH as a disorder of the cerebral vasculature, glymphatics, and most of all, the distribution of intracranial pulsatility, provides a novel framework through which to understand and manage this condition, one which requires further investigation.

  View details for DOI 10.1136/bmjno-2024-000804

  View details for PubMedID 39430787

  View details for PubMedCentralID PMC11487818

• Sequential Detection of Anomalies in Noisy Outputs of an Unknown Function Using Gaussian and Yule-Simon Processes ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Yang, L., Butler, K., Djurić, P. M. 2024: 7205-7209

  View details for DOI 10.1109/ICASSP48485.2024.10446227

• A quantitative model of the cerebral windkessel and its relevance to disorders of intracranial dynamics Journal of Neurosurgery: Pediatrics Egnor, M., Yang, L., Mani, R. M., Fiore, S. M., Djurić, P. M. 2023; 32 (3): 302–311
• Why don't ventricles dilate in pseudotumor cerebri? A circuit model of the cerebral windkessel. Journal of neurosurgery. Pediatrics Wang, Z., Yang, L., Djurić, P. M., Egnor, M. R. 2022; 29 (6): 719-726

  Abstract

  Pseudotumor cerebri is a disorder of intracranial dynamics characterized by elevated intracranial pressure (ICP) and chronic cerebral venous hypertension without structural abnormalities. A perplexing feature of pseudotumor is the absence of the ventriculomegaly found in obstructive hydrocephalus, although both diseases are associated with increased resistance to cerebrospinal fluid (CSF) resorption. Traditionally, the pathophysiology of ventricular dilation and obstructive hydrocephalus has been attributed to the backup of CSF due to impaired absorption, and it is unclear why backup of CSF with resulting ventriculomegaly would not occur in pseudotumor. In this study, the authors used an electrical circuit model to simulate the cerebral windkessel effect and explain the presence of ventriculomegaly in obstructive hydrocephalus but not in pseudotumor cerebri.The cerebral windkessel is a band-stop filter that dampens the arterial blood pressure pulse in the cranium. The authors used a tank circuit with parallel inductance and capacitance to model the windkessel. The authors distinguished the smooth flow of blood and CSF and the pulsatile flow of blood and CSF by using direct current (DC) and alternating current (AC) sources, respectively. The authors measured the dampening notch from ABP to ICP as the band-stop filter of the windkessel.In obstructive hydrocephalus, loss of CSF pathway volume impaired the flow of AC power in the cranium and caused windkessel impairment, to which ventriculomegaly is an adaptation. In pseudotumor, venous hypertension affected DC power flow in the capillaries but did not affect AC power or the windkessel, therefore obviating the need for adaptive ventriculomegaly.In pseudotumor, the CSF spaces are unaffected and the windkessel remains effective. Therefore, ventricles remain normal in size. In hydrocephalus, the windkessel, which depends on the flow of AC power in patent CSF spaces, is impaired, and the ventricles dilate as an adaptive process to restore CSF pathway volume. The windkessel model explains both ventriculomegaly in obstructive hydrocephalus and the lack of ventriculomegaly in pseudotumor. This model provides a novel understanding of the pathophysiology of disorders of CSF dynamics and has significant implications in clinical management.

  View details for DOI 10.3171/2022.1.PEDS21527

  View details for PubMedID 35303694

• UNSUPERVISED CLUSTERING AND ANALYSIS OF CONTRACTION-DEPENDENT FETAL HEART RATE SEGMENTS. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) Yang, L., Heiselman, C., Quirk, J. G., Djurić, P. M. 2022; 2022

  Abstract

  The computer-aided interpretation of fetal heart rate (FHR) and uterine contraction (UC) has not been developed well enough for wide use in delivery rooms. The main challenges still lie in the lack of unclear and nonstandard labels for cardiotocography (CTG) recordings, and the timely prediction of fetal state during monitoring. Rather than traditional supervised approaches to FHR classification, this paper demonstrates a way to understand the UC-dependent FHR responses in an unsupervised manner. In this work, we provide a complete method for FHR-UC segment clustering and analysis via the Gaussian process latent variable model, and density-based spatial clustering. We map the UC-dependent FHR segments into a space with a visual dimension and propose a trajectory-based FHR interpretation method. Three metrics of FHR trajectory are defined and an open-access CTG database is used for testing the proposed method.

  View details for DOI 10.1109/icassp43922.2022.9747598

  View details for PubMedID 36035504

  View details for PubMedCentralID PMC9415917

• Unsupervised Detection of Anomalies in Fetal Heart Rate Tracings using Phase Space Reconstruction. Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference) Yang, L., Ajirak, M., Heiselman, C., Quirk, J. G., Djurić, P. M. 2021; 2021: 1321-1325

  Abstract

  Detection of anomalies in time series is still a challenging problem. In this paper, we provide a new approach to unsupervised detection of anomalies in time series based on the concept of phase space reconstruction and manifolds. We propose a rotation-insensitive metric for quantifying the similarity of manifolds and a method that uses it for estimating the probability of an outlier. The proposed method does not rely on any features and can be used for signals with variable lengths. We tested it on both synthetic signals and real fetal heart rate tracings. The method has promising performance and can be used for interpreting the severity of fetal asphyxia.

  View details for DOI 10.23919/eusipco54536.2021.9616264

  View details for PubMedID 35233348

  View details for PubMedCentralID PMC8884191

• IDENTIFICATION OF UTERINE CONTRACTIONS BY AN ENSEMBLE OF GAUSSIAN PROCESSES. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) Yang, L., Heiselman, C., Quirk, J. G., Djurić, P. M. 2021; 2021

  Abstract

  Identifying uterine contractions with the aid of machine learning methods is necessary vis-á-vis their use in combination with fetal heart rates and other clinical data for the assessment of a fetus wellbeing. In this paper, we study contraction identification by processing noisy signals due to uterine activities. We propose a complete four-step method where we address the imbalanced classification problem with an ensemble Gaussian process classifier, where the Gaussian process latent variable model is used as a decision-maker. The results of both simulation and real data show promising performance compared to existing methods.

  View details for DOI 10.1109/icassp39728.2021.9414041

  View details for PubMedID 34712103

  View details for PubMedCentralID PMC8547336

• CLASS-IMBALANCED CLASSIFIERS USING ENSEMBLES OF GAUSSIAN PROCESSES AND GAUSSIAN PROCESS LATENT VARIABLE MODELS. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) Yang, L., Heiselman, C., Quirk, J. G., Djurić, P. M. 2021; 2021

  Abstract

  Classification with imbalanced data is a common and challenging problem in many practical machine learning problems. Ensemble learning is a popular solution where the results from multiple base classifiers are synthesized to reduce the effect of a possibly skewed distribution of the training set. In this paper, binary classifiers based on Gaussian processes are chosen as bases for inferring the predictive distributions of test latent variables. We apply a Gaussian process latent variable model where the outputs of the Gaussian processes are used for making the final decision. The tests of the new method in both synthetic and real data sets show improved performance over standard approaches.

  View details for DOI 10.1109/icassp39728.2021.9414754

  View details for PubMedID 34712104

  View details for PubMedCentralID PMC8547341

• Particle Filtering Under General Regime Switching El-Laham, Y., Yang, L., Djuric, P. M., Bugallo, M. F., IEEE IEEE. 2021: 2378-2382

  View details for Web of Science ID 000632622300479

• PARTICLE GIBBS SAMPLING FOR REGIME-SWITCHING STATE-SPACE MODELS El-Laham, Y., Yang, L., Lynch, H. J., Djuric, P. M., Bugallo, M. F., IEEE IEEE. 2021: 5579-5583

  View details for DOI 10.1109/ICASSP39728.2021.9414875

  View details for Web of Science ID 000704288405169

• INDOOR ALTITUDE ESTIMATION OF UNMANNED AERIAL VEHICLES USING A BANK OF KALMAN FILTERS Yang, L., Wang, H., El-Laham, Y., Lamas Fonte, J., Perez, D., Bugallo, M. F., IEEE IEEE. 2020: 5455-5459

  View details for DOI 10.1109/icassp40776.2020.9054203

  View details for Web of Science ID 000615970405143

• MOVING TARGET LOCALIZATION IN MULTISTATIC SONAR USING TIME DELAYS, DOPPLER SHIFTS AND ARRIVAL ANGLES Yang, L., Yang, L., Ho, K. C., IEEE IEEE. 2017: 3399-3403

  View details for Web of Science ID 000414286203113

• TDOA-FDOA source geolocation using moving horizon estimation with satellite location errors 2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Shan, C., Yang, L., Yang, L., Li, X., Li, W. 2017

  View details for DOI 10.1109/PACRIM.2017.8121932

• Moving Target Localization in Multistatic Sonar by Differential Delays and Doppler Shifts IEEE SIGNAL PROCESSING LETTERS Yang, L., Yang, L., Ho, K. C. 2016; 23 (9): 1160-1164

  View details for DOI 10.1109/LSP.2016.2582043

  View details for Web of Science ID 000381454400002