Machine learning and the prediction of suicide in psychiatric populations: a systematic review | Translational Psychiatry – Nature.com
Fazel S, Runeson B. Suicide. N. Engl J Med. 2020;382:26674.
Article PubMed PubMed Central Google Scholar
Bachmann S. Epidemiology of suicide and the psychiatric perspective. Int J Environ Res Public Health. 2018. https://doi.org/10.3390/IJERPH15071425.
Sanderson M, Bulloch AG, Wang JL, Williams KG, Williamson T, Patten SB. Predicting death by suicide following an emergency department visit for parasuicide with administrative health care system data and machine learning. EClinicalMedicine. 2020. https://doi.org/10.1016/j.eclinm.2020.100281.
Walsh CG, Ribeiro JD, Franklin JC. Predicting risk of suicide attempts over time through machine learning. Clin Psychol Sci. 2017;5:45769.
Article Google Scholar
Bauer BW, Law KC, Rogers ML, Capron DW, Bryan CJ. Editorial overview: analytic and methodological innovations for suicide-focused research. Suicide Life Threat Behav. 2021;51:57.
Article PubMed Google Scholar
Gradus JL, Rosellini AJ, Horvth-Puh E, Street AE, Galatzer-Levy I, Jiang T, et al. Prediction of sex-specific suicide risk using machine learning and single-Payer Health Care Registry Data from Denmark. JAMA Psychiatry. 2020;77:2534.
Article PubMed Google Scholar
Voros V, Tenyi T, Nagy A, Fekete S, Osvath P. Crisis concept re-loaded?-The recently described suicide-specific syndromes may help to better understand suicidal behavior and assess imminent suicide risk more effectively. Front Psychiatry. 2021. https://doi.org/10.3389/FPSYT.2021.598923.
Galynker I, Yaseen ZS, Cohen A, Benhamou O, Hawes M, Briggs J. Prediction of suicidal behavior in high risk psychiatric patients using an assessment of acute suicidal state: the suicide crisis inventory. Depress Anxiety. 2017;34:14758.
Article PubMed Google Scholar
Franklin JC, Ribeiro JD, Fox KR, Bentley KH, Kleiman EM, Huang X, et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017;143:187232.
Article PubMed Google Scholar
Beck AT, Steer RA, Kovacs M, Garrison B. Hopelessness and eventual suicide: a 10-year prospective study of patients hospitalized with suicidal ideation. Am J Psychiatry. 1985;142:55963.
Article CAS PubMed Google Scholar
McHugh CM, Large MM. Can machine-learning methods really help predict suicide? Curr Opin Psychiatry. 2020;33:36974.
Article PubMed Google Scholar
Porcelli S, Marsano A, Caletti E, Sala M, Abbiati V, Bellani M, et al. Temperament and character inventory in bipolar disorder versus healthy controls and modulatory effects of 3 key functional gene variants. Neuropsychobiology. 2017;76:20921.
Article CAS PubMed Google Scholar
Grassi M, Perna G, Caldirola D, Schruers K, Duara R, Loewenstein DA. A clinically-translatable machine learning algorithm for the prediction of Alzheimers disease conversion in individuals with mild and premild cognitive impairment. J Alzheimers Dis. 2018;61:155573.
Article Google Scholar
Russak AJ, Chaudhry F, De Freitas JK, Baron G, Chaudhry FF, Bienstock S, et al. Machine learning in cardiology-ensuring clinical impact lives up to the hype. J Cardiovasc Pharm Ther. 2020;25:37990.
Article Google Scholar
Corke M, Mullin K, Angel-Scott H, Xia S, Large M. Meta-analysis of the strength of exploratory suicide prediction models; from clinicians to computers. BJPsych Open. 2021. https://doi.org/10.1192/BJO.2020.162.
Fazel S, OReilly L. Machine learning for suicide research-can it improve risk factor identification? JAMA Psychiatry. 2020;77:1314.
Article PubMed PubMed Central Google Scholar
Boudreaux ED, Rundensteiner E, Liu F, Wang B, Larkin C, Agu E, et al. Applying machine learning approaches to suicide prediction using healthcare data: overview and future directions. Front Psychiatry. 2021. https://doi.org/10.3389/FPSYT.2021.707916.
Jacobson NC, Yom-Tov E, Lekkas D, Heinz M, Liu L, Barr PJ. Impact of online mental health screening tools on help-seeking, care receipt, and suicidal ideation and suicidal intent: evidence from internet search behavior in a large U.S. cohort. J Psychiatr Res. 2022;145:27683.
Article PubMed Google Scholar
Holmstrand C, Bogren M, Mattisson C, Brdvik L. Long-term suicide risk in no, one or more mental disorders: the Lundby Study 19471997. Acta Psychiatr Scand. 2015;132:45969.
Article CAS PubMed PubMed Central Google Scholar
Modai I, Kuperman J, Goldberg I, Goldish M, Mendel S. Suicide risk factors and suicide vulnerability in various major psychiatric disorders. Med Inform Internet Med. 2009;29:6574.
Modai I, Kuperman J, Goldberg I, Goldish M, Mendel S. Fuzzy logic detection of medically serious suicide attempt records in major psychiatric disorders. J Nerv Ment Dis. 2004;192:70810.
Article PubMed Google Scholar
ORourke MC, Siddiqui W. Suicide screening and prevention. StatPearls. 2019. http://www.ncbi.nlm.nih.gov/pubmed/30285348.
McIntyre RS, Berk M, Brietzke E, Goldstein BI, Lpez-Jaramillo C, Kessing LV, et al. Bipolar disorders. Lancet. 2020;396:184156.
Article CAS PubMed Google Scholar
Wiebenga JXM, Dickhoff J, Mrelle SYM, Eikelenboom M, Heering HD, Gilissen R, et al. Prevalence, course, and determinants of suicide ideation and attempts in patients with a depressive and/or anxiety disorder: a review of NESDA findings. J Affect Disord. 2021;283:26777.
Article PubMed Google Scholar
Mitchell SM, Cero I, Littlefield AK, Brown SL. Using categorical data analyses in suicide research: considering clinical utility and practicality. Suicide Life Threat Behav. 2021;51:7687.
Article PubMed PubMed Central Google Scholar
Page MJ, Mckenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021. https://doi.org/10.1136/bmj.n71.
Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ. 2015. https://doi.org/10.1136/bmj.g7594.
Tiet QQ, Ilgen MA, Byrnes HF, Moos RH. Suicide attempts among substance use disorder patients: an initial step toward a decision tree for suicide management. Alcohol Clin Exp Res. 2006;30:9981005.
Article PubMed Google Scholar
Jiang T, Rosellini AJ, Horvth-Puh E, Shiner B, Street AE, Lash TL, et al. Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark. Br J Psychiatry. 2021;219:4407.
Parghi N, Chennapragada L, Barzilay S, Newkirk S, Ahmedani B, Lok B, et al. Assessing the predictive ability of the Suicide Crisis Inventory for near-term suicidal behavior using machine learning approaches. Int J Methods Psychiatr Res. 2021. https://doi.org/10.1002/MPR.1863.
McMullen L, Parghi N, Rogers ML, Yao H, Bloch-Elkouby S, Galynker I. The role of suicide ideation in assessing near-term suicide risk: a machine learning approach. Psychiatry Res. 2021. https://doi.org/10.1016/J.PSYCHRES.2021.114118.
Zelkowitz RL, Jiang T, Horvth-Puh E, Street AE, Lash TL, Srensen HT, et al. Predictors of nonfatal suicide attempts within 30 days of discharge from psychiatric hospitalization: sex-specific models developed using population-based registries. J Affect Disord. 2022;306:2608.
Article PubMed PubMed Central Google Scholar
Chen Q, Zhang-James Y, Barnett EJ, Lichtenstein P, Jokinen J, DOnofrio BM, et al. Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: a machine learning study using Swedish national registry data. PLoS Med. 2020. https://doi.org/10.1371/JOURNAL.PMED.1003416.
Tran T, Luo W, Phung D, Harvey R, Berk M, Kennedy RL, et al. Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments. BMC Psychiatry. 2014. https://doi.org/10.1186/1471-244X-14-76.
Coley RY, Walker RL, Cruz M, Simon GE, Shortreed SM. Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm. Biom J. 2021;63:137588.
Article MathSciNet PubMed PubMed Central Google Scholar
Miranda O, Fan P, Qi X, Yu Z, Ying J, Wang H, et al. DeepBiomarker: identifying important lab tests from electronic medical records for the prediction of suicide-related events among PTSD patients. J Pers Med. 2022;12:524.
Article PubMed PubMed Central Google Scholar
Nock MK, Millner AJ, Ross EL, Kennedy CJ, Al-Suwaidi M, Barak-Corren Y, et al. Prediction of suicide attempts using clinician assessment, patient self-report, and electronic health records. JAMA Netw Open. 2022. https://doi.org/10.1001/JAMANETWORKOPEN.2021.44373.
Edgcomb JB, Thiruvalluru R, Pathak J, Brooks JO. Machine learning to differentiate risk of suicide attempt and self-harm after general medical hospitalization of women with mental illness. Med Care. 2021;59:S58S64.
Article PubMed PubMed Central Google Scholar
Kessler RC, Warner CH, Ivany C, Petukhova MV, Rose S, Bromet EJ, et al. Predicting suicides after psychiatric hospitalization in US army soldiers: the Army study to assess risk and resilience in servicemembers (Army STARRS). JAMA Psychiatry. 2015;72:4957.
Article PubMed PubMed Central Google Scholar
Jordan JT, McNiel DE. Characteristics of a suicide attempt predict who makes another attempt after hospital discharge: a decision-tree investigation. Psychiatry Res. 2018;268:31722.
Article PubMed Google Scholar
Xu Z, Zhang Q, Yip PSF. Predicting post-discharge self-harm incidents using disease comorbidity networks: a retrospective machine learning study. J Affect Disord. 2020;277:4029.
Article PubMed Google Scholar
Niculescu AB, Levey DF, Phalen PL, Le-Niculescu H, Dainton HD, Jain N, et al. Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach. Mol Psychiatry. 2015;20:126685.
Article CAS PubMed PubMed Central Google Scholar
Levey DF, Niculescu EM, Le-Niculescu H, Dainton HL, Phalen PL, Ladd TB, et al. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment. Mol Psychiatry. 2016;21:76885.
Article CAS PubMed Google Scholar
Kessler RC, Stein MB, Petukhova MV, Bliese P, Bossarte RM, Bromet EJ, et al. Predicting suicides after outpatient mental health visits in the Army study to assess risk and resilience in servicemembers (Army STARRS). Mol Psychiatry. 2017;22:54451.
Article CAS PubMed Google Scholar
Cook BL, Progovac AM, Chen P, Mullin B, Hou S, Baca-Garcia E. Novel use of natural language processing (NLP) to predict suicidal ideation and psychiatric symptoms in a text-based mental health intervention in Madrid. Comput Math Methods Med. 2016. https://doi.org/10.1155/2016/8708434.
Setoyama D, Kato TA, Hashimoto R, Kunugi H, Hattori K, Hayakawa K, et al. Plasma metabolites predict severity of depression and suicidal ideation in psychiatric patients-a multicenter pilot analysis. PLoS ONE. 2016. https://doi.org/10.1371/journal.pone.0165267.
Chen J, Zhang X, Qu Y, Peng Y, Song Y, Zhuo C, et al. Exploring neurometabolic alterations in bipolar disorder with suicidal ideation based on proton magnetic resonance spectroscopy and machine learning technology. Front Neurosci. 2022. https://doi.org/10.3389/FNINS.2022.944585.
Peis I, Olmos PM, Vera-Varela C, Barrigon ML, Courtet P, Baca-Garcia E, et al. Deep sequential models for suicidal ideation from multiple source data. IEEE J Biomed Heal Inform. 2019;23:228693.
Article Google Scholar
Weng J-C, Lin T-Y, Tsai Y-H, Cheok MT, Chang Y-PE, Chen VC-H. An autoencoder and machine learning model to predict suicidal ideation with brain structural imaging. J Clin Med. 2020;9:658.
Article PubMed PubMed Central Google Scholar
Cusick M, Adekkanattu P, Campion TR, Sholle ET, Myers A, Banerjee S, et al. Using weak supervision and deep learning to classify clinical notes for identification of current suicidal ideation. J Psychiatr Res. 2021;136:95102.
Article PubMed PubMed Central Google Scholar
Ge F, Jiang J, Wang Y, Yuan C, Zhang W. Identifying suicidal ideation among chinese patients with major depressive disorder: evidence from a real-world hospital-based study in China. Neuropsychiatr Dis Treat. 2020;16:66572.
Article PubMed PubMed Central Google Scholar
Tubo-Fungueirio M, Cernadas E, Gonalves F, Segalas C, Bertoln S, Mar-Barrutia L, et al. Viability study of machine learning-based prediction of COVID-19 pandemic impact in obsessive-compulsive disorder patients. Front Neuroinform. 2022. https://doi.org/10.3389/FNINF.2022.807584.
Hong S, Liu YS, Cao B, Cao J, Ai M, Chen J, et al. Identification of suicidality in adolescent major depressive disorder patients using sMRI: a machine learning approach. J Affect Disord. 2021;280:7276.
Article PubMed Google Scholar
Yang J, Palaniyappan L, Xi C, Cheng Y, Fan Z, Chen C, et al. Aberrant integrity of the cortico-limbic-striatal circuit in major depressive disorder with suicidal ideation. J Psychiatr Res. 2022;148:27785.
Article PubMed Google Scholar
Chen S, Zhang X, Lin S, Zhang Y, Xu Z, Li Y, et al. Suicide risk stratification among major depressed patients based on a machine learning approach and whole-brain functional connectivity. J Affect Disord. 2022;322:1739.
Article PubMed Google Scholar
Morales S, Barros J, Echvarri O, Garca F, Osses A, Moya C, et al. Acute mental discomfort associated with suicide behavior in a clinical sample of patients with affective disorders: ascertaining critical variables using artificial intelligence tools. Front Psychiatry. 2017. https://doi.org/10.3389/fpsyt.2017.00007.
Fan P, Guo X, Qi X, Matharu M, Patel R, Sakolsky D, et al. Prediction of suiciderelated events by analyzing electronic medical records from PTSD patients with bipolar disorder. Brain Sci. 2020;10:130.
Article Google Scholar
Shao R, Gao M, Lin C, Huang CM, Liu HL, Toh CH, et al. Multimodal neural evidence on the corticostriatal underpinning of suicidality in late-life depression. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021. https://doi.org/10.1016/J.BPSC.2021.11.011.
Chen VC-H, Wong F-T, Tsai Y-H, Cheok MT, Chang Y-PE, McIntyre RS, et al. Convolutional neural network-based deep learning model for predicting differential suicidality in depressive patients using brain generalized q-sampling imaging. J Clin Psychiatry. 2021. https://doi.org/10.4088/JCP.19M13225.
Xu M, Zhang X, Li Y, Chen S, Zhang Y, Zhou Z, et al. Identification of suicidality in patients with major depressive disorder via dynamic functional network connectivity signatures and machine learning. Transl Psychiatry. 2022. https://doi.org/10.1038/S41398-022-02147-X.
Kumar P, Nestsiarovich A, Nelson SJ, Kerner B, Perkins DJ, Lambert CG. Imputation and characterization of uncoded self-harm in major mental illness using machine learning. J Am Med Inform Assoc. 2020;27:13646.
Article PubMed Google Scholar
Obeid JS, Dahne J, Christensen S, Howard S, Crawford T, Frey LJ, et al. Identifying and predicting intentional self-harm in electronic health record clinical notes: deep learning approach. JMIR Med Informatics. 2020. https://doi.org/10.2196/17784.
See original here:
Machine learning and the prediction of suicide in psychiatric populations: a systematic review | Translational Psychiatry - Nature.com
- Optimization of wear parameters for ECAP-processed ZK30 alloy using response surface and machine learning ... - Nature.com - April 22nd, 2024 [April 22nd, 2024]
- Machine learning approach predicts heart failure outcome risk - HealthITAnalytics.com - April 22nd, 2024 [April 22nd, 2024]
- Practical approaches in evaluating validation and biases of machine learning applied to mobile health studies ... - Nature.com - April 22nd, 2024 [April 22nd, 2024]
- Application of power-law committee machine to combine five machine learning algorithms for enhanced oil recovery ... - Nature.com - April 22nd, 2024 [April 22nd, 2024]
- Free tool uses machine learning to pick better molecules for testing new reactions - Chemical & Engineering News - April 22nd, 2024 [April 22nd, 2024]
- Automated Analysis of Nuclear Parameters in Oral Exfoliative Cytology Using Machine Learning - Cureus - April 22nd, 2024 [April 22nd, 2024]
- An AI Ethics Researcher's Take On The Future Of Machine Learning In The Art World - SlashGear - April 22nd, 2024 [April 22nd, 2024]
- Enhancing Emotion Recognition in Users with Cochlear Implant Through Machine Learning and EEG Analysis - Physician's Weekly - April 22nd, 2024 [April 22nd, 2024]
- Imageomics Applies AI and Vision Advancements to Biological Questions - Photonics.com - April 22nd, 2024 [April 22nd, 2024]
- Machine learning reveals the control mechanics of an insect wing hinge - Nature.com - April 22nd, 2024 [April 22nd, 2024]
- The Future of ML Development Services: Trends and Predictions - FinSMEs - April 22nd, 2024 [April 22nd, 2024]
- CSRWire - Island Conservation Harnesses Machine Learning Solutions From Lenovo and NVIDIA To Restore Island ... - CSRwire.com - April 22nd, 2024 [April 22nd, 2024]
- Investigation of the effectiveness of a classification method based on improved DAE feature extraction for hepatitis C ... - Nature.com - April 22nd, 2024 [April 22nd, 2024]
- Machine Learning Uncovers New Ways to Kill Bacteria With Non-Antibiotic Drugs - ScienceAlert - April 22nd, 2024 [April 22nd, 2024]
- Formal Interaction Model (FIM): A Mathematics-based Machine Learning Model that Formalizes How AI and Users Shape One Another - MarkTechPost - April 22nd, 2024 [April 22nd, 2024]
- A secure approach to generative AI with AWS | Amazon Web Services - AWS Blog - April 22nd, 2024 [April 22nd, 2024]
- Imbalanced Learn: the Python library for rebuilding ML datasets - DataScientest - April 22nd, 2024 [April 22nd, 2024]
- AI has a lot of terms. We've got a glossary for what you need to know - Quartz - April 22nd, 2024 [April 22nd, 2024]
- Texxa AI, Where ideas take flight: Revolutionizing AI Solutions for Businesses and Individuals - GlobeNewswire - April 22nd, 2024 [April 22nd, 2024]
- Using machine learning to identify patients with cancer that would benefit from immunotherapy - Medical Xpress - April 22nd, 2024 [April 22nd, 2024]
- Researchers at Stanford University Explore Direct Preference Optimization (DPO): A New Frontier in Machine Learning and Human Feedback - MarkTechPost - April 22nd, 2024 [April 22nd, 2024]
- Machine Learning Helps Scientists Locate the Neurological Origin of Psychosis - ExtremeTech - April 22nd, 2024 [April 22nd, 2024]
- Slack delivers native and secure generative AI powered by Amazon SageMaker JumpStart | Amazon Web Services - AWS Blog - April 22nd, 2024 [April 22nd, 2024]
- Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform - Nature.com - March 20th, 2024 [March 20th, 2024]
- AI reveals the complexity of a simple birdsong - The Washington Post - March 20th, 2024 [March 20th, 2024]
- Researchers from MIT and Harvard Developed UNITS: A Unified Machine Learning Model for Time Series Analysis that Supports a Universal Task... - March 20th, 2024 [March 20th, 2024]
- Undergraduate Researchers Help Unlock Lessons of Machine Learning and AI - College of Natural Sciences - March 20th, 2024 [March 20th, 2024]
- Machine Learning Accelerates the Simulation of Dynamical Fields - Eos - March 20th, 2024 [March 20th, 2024]
- Inter hospital external validation of interpretable machine learning based triage score for the emergency department ... - Nature.com - March 20th, 2024 [March 20th, 2024]
- HEAL: A framework for health equity assessment of machine learning performance - Google Research - March 20th, 2024 [March 20th, 2024]
- Expert on how machine learning could lead to improved outcomes in urology - Urology Times - March 20th, 2024 [March 20th, 2024]
- Unlock the potential of generative AI in industrial operations | Amazon Web Services - AWS Blog - March 20th, 2024 [March 20th, 2024]
- Optimize price-performance of LLM inference on NVIDIA GPUs using the Amazon SageMaker integration with NVIDIA ... - AWS Blog - March 20th, 2024 [March 20th, 2024]
- Orange isn't building its own AI foundation model here's why - Light Reading - March 20th, 2024 [March 20th, 2024]
- Wall Street's Favorite Machine Learning Stocks? 3 Names That Could Make You Filthy Rich - InvestorPlace - March 20th, 2024 [March 20th, 2024]
- Edge Impulse machine learning platform adds support for NVIDIA TAO Toolkit and Omniverse - CNX Software - March 20th, 2024 [March 20th, 2024]
- MIT Researchers Developed an Image Dataset that Allows Them to Simulate Peripheral Vision in Machine Learning Models - MarkTechPost - March 20th, 2024 [March 20th, 2024]
- 18 Cutting-Edge Artificial Intelligence Applications in 2024 - Simplilearn - March 20th, 2024 [March 20th, 2024]
- Machine-learning-based global optimization of microwave passives with variable-fidelity EM models and response ... - Nature.com - March 20th, 2024 [March 20th, 2024]
- Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency-related traits in ... - Nature.com - March 20th, 2024 [March 20th, 2024]
- PyCaret: Everything you need to know about this Python library - DataScientest - March 20th, 2024 [March 20th, 2024]
- Crypto Entities That Neglect AI and Machine Learning Investment Will Lag Behind, Warns Binance CTO Bitcoin News - Bitcoin.com News - March 20th, 2024 [March 20th, 2024]
- VictoriaMetrics Machine Learning takes monitoring to the next level - The Bakersfield Californian - March 20th, 2024 [March 20th, 2024]
- How Marketers Can Elevate Creative Performance with AI-Driven Format Optimisation - ExchangeWire - March 20th, 2024 [March 20th, 2024]
- Revolutionizing carbon neutrality: Machine learning paves the way for advanced CO reduction catalysts - EurekAlert - March 20th, 2024 [March 20th, 2024]
- BurstAttention: A Groundbreaking Machine Learning Framework that Transforms Efficiency in Large Language Models with Advanced Distributed Attention... - March 20th, 2024 [March 20th, 2024]
- Construction of environmental vibration prediction model for subway transportation based on machine learning ... - Nature.com - March 20th, 2024 [March 20th, 2024]
- Introducing 'Get started with generative AI on AWS: A guide for public sector organizations' | Amazon Web Services - AWS Blog - March 20th, 2024 [March 20th, 2024]
- Generative deep learning for the development of a type 1 diabetes simulator | Communications Medicine - Nature.com - March 20th, 2024 [March 20th, 2024]
- Integrating core physics and machine learning for improved parameter prediction in boiling water reactor operations ... - Nature.com - March 11th, 2024 [March 11th, 2024]
- Top AI Certification Courses to Enroll in 2024 - Analytics Insight - March 11th, 2024 [March 11th, 2024]
- Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions - ScienceDirect.com - March 11th, 2024 [March 11th, 2024]
- Artificial Intelligence Market towards a USD 2,745 bn by 2032 - Market.us Scoop - Market News - March 11th, 2024 [March 11th, 2024]
- Data Maturation Represents the Essential Reason for Deploying Machine Learning Today | By Adam Mogelonsky - Hospitality Net - March 11th, 2024 [March 11th, 2024]
- The Top 3 Machine Learning Stocks to Buy in March 2024 - InvestorPlace - March 11th, 2024 [March 11th, 2024]
- How to Learn the Math Needed for Data Science - Towards Data Science - March 11th, 2024 [March 11th, 2024]
- This AI Paper from Huawei Introduces DenseSSM: A Novel Machine Learning Approach to Enhance the Flow of Hidden Information between Layers in State... - March 11th, 2024 [March 11th, 2024]
- Machine learning algorithms show applications in OAB, antibiotic resistance - Urology Times - March 11th, 2024 [March 11th, 2024]
- Scientists develop new machine learning method for modeling chemical reactions - Phys.org - March 11th, 2024 [March 11th, 2024]
- Machine learning developed a CD8+ exhausted T cells signature for predicting prognosis, immune infiltration and drug ... - Nature.com - March 11th, 2024 [March 11th, 2024]
- Single Transit Detection In Kepler With Machine Learning And Onboard Spacecraft Diagnostics - Astrobiology - Astrobiology News - March 11th, 2024 [March 11th, 2024]
- Meta AI Proposes Wukong: A New Machine Learning Architecture that Exhibits Effective Dense Scaling Properties Towards a Scaling Law for Large-Scale... - March 11th, 2024 [March 11th, 2024]
- Putting the AI in NIA: New opportunities in artificial intelligence - National Institute on Aging - March 11th, 2024 [March 11th, 2024]
- Revolutionizing LLM Training with GaLore: A New Machine Learning Approach to Enhance Memory Efficiency without Compromising Performance - MarkTechPost - March 11th, 2024 [March 11th, 2024]
- Uncertainty-aware deep learning for trustworthy prediction of long-term outcome after endovascular thrombectomy ... - Nature.com - March 11th, 2024 [March 11th, 2024]
- AI Engineer Salary: The Lucrative World of AI Engineering - Simplilearn - March 11th, 2024 [March 11th, 2024]
- Multimodal artificial intelligence-based pathogenomics improves survival prediction in oral squamous cell carcinoma ... - Nature.com - March 11th, 2024 [March 11th, 2024]
- Northrop Grumman Partners to Advance Deep Sensing for the US Army | Northrop Grumman - Northrop Grumman Newsroom - March 11th, 2024 [March 11th, 2024]
- Global cellular IoT connections to grow 90% to 6.5 bn by 2028: Juniper Research - ETTelecom - March 11th, 2024 [March 11th, 2024]
- Enhancing statistical reliability of weather forecasts with machine learning - Phys.org - March 11th, 2024 [March 11th, 2024]
- Inside AI: Talking to the Data - Inside Unmanned Systems - March 11th, 2024 [March 11th, 2024]
- Anemond's Factoid 2 is an experimental sampler plugin that uses machine learning to "decompose", remix and ... - MusicRadar - March 11th, 2024 [March 11th, 2024]
- Advancing Chemistry with AI: New Model for Simulating Diverse Organic Reactions - Lab Manager Magazine - March 11th, 2024 [March 11th, 2024]
- Generative AI: Understand the challenges to realize the opportunities | Amazon Web Services - AWS Blog - March 11th, 2024 [March 11th, 2024]
- How To Specialize in Artificial Intelligence - Troy Today - Troy University - March 11th, 2024 [March 11th, 2024]
- Google DeepMind Introduces Two Unique Machine Learning Models, Hawk And Griffin, Combining Gated Linear Recurrences With Local Attention For Efficient... - March 11th, 2024 [March 11th, 2024]
- Unlocking Innovation: AWS and Anthropic push the boundaries of generative AI together | Amazon Web Services - AWS Blog - March 11th, 2024 [March 11th, 2024]
- Introducing Microsoft's AI Red Team And PyRIT - AiThority - March 11th, 2024 [March 11th, 2024]
- Unveiling the World of Artificial Intelligence: A Beginner's Guide - Medium - January 3rd, 2024 [January 3rd, 2024]
- How machine learning might unlock earthquake prediction - MIT Technology Review - January 3rd, 2024 [January 3rd, 2024]
Tags: