人工知能
時代遅れの緊急プロトコル、機械学習で近代化が期待される
New データ from Osaka University has shown that machine learning’s rapidly increasing capabilities may now extend to emergency situations. 研究チームは that the technology can now effectively assist in determining appropriate candidates for Tranexamic Acid, reducing mortality rates among trauma patients.
トラネキサム酸（TXA）とは何か？
Most medications are simply treatments for some sort of condition. A few, however, can be truly lifesaving. One of these is Tranexamic Acid, or ‘TXA’. On its simplest level, TXA is given to patients to stop extensive bleeding, typically stemming from some sort of trauma.
より詳しく見ると、TXAは体内での血液凝固を促進することで出血を減少・予防します。これは、血栓形成に必要なタンパク質であるフィブリンを分解する酵素プラスミンの生成を阻害することによって実現されます。
Normally, the presence of plasmin is a good thing, as it prevents excessive clotting and a litany of ailments (e.g., strokes, pulmonary embolism, deep vein thrombosis, myocardial infarction, etc,.) that may result. However, in an emergency situation where bleeding needs to be controlled, TXA’s ability to prevent its formation is crucial.
機械学習による緊急時の命救助
Whether it is a frontline Paramedic working to stabilize a patient in the back of a moving ambulance, or a Nurse working alongside a team of healthcare professionals in an emergency room, TXA remains an important tool for managing unchecked bleeding resulting from trauma. It is important to recognize, though, that TXA is not appropriate for every patient, as it is often accompanied by serious side-effects, making the determination for delivery a difficult one.
TXAが潜在的な副作用のために全ての患者に有益ではないことを認識し、前述の研究は、TXA治療から最も恩恵を受ける可能性の高い外傷患者の特定サブグループの特定に焦点を当てました。将来的には、この候補者の特定能力が、投与適格性を判断する既存プロトコルの近代化に重要な役割を果たす可能性があります。
機械学習手法を用いて、研究者は日本外傷データバンクの5万人以上の患者データを分析し、8つの異なる外傷フェノタイプ（観察可能な特性に基づくグループ）を特定しました。その後、これらのフェノタイプに対するTXAの院内死亡率への影響を検証しました。結果は、特定のサブグループではTXA投与により死亡率が有意に低下する一方、他のグループでは効果が見られないことを示しました。
The study underscores the diverse presentations of trauma patients, whose injuries vary widely in type and severity, making it challenging to predict treatment effectiveness on an individual basis. The goal of this research is to enhance personalized care for trauma patients, thereby improving the overall quality of care and survival rates in this high-risk population. This approach to patient-specific treatment could lead to more effective use of TXA in trauma care, reducing unnecessary side effects and optimizing outcomes – all thanks to machine learning.
機械学習：破壊的技術全般の中心的触媒
This study is the latest in a growing crop of examples highlighting how subsets of artificial intelligence, like machine learning, can excel as a central catalyst or ‘core technology’ across nearly any sector – a realization which was underscored in Ark Invest’s ‘Big Ideas 2024’.
Much of this is attributed to AI’s ability to process and recognize patterns within vast amounts of data. It can do so more efficiently than any human and is advancing itself quicker and quicker.
機械学習の専門家
While it may be some time before machine learning is used to determine whether a patient should be given TXA is put into practice, there are multiple companies already working to develop the technology further. In fact, some have already begun to incorporate it into other facets of healthcare that are just as important.
*Figures provided below were accurate at the time of writing and are subject to change. Any potential investor should verify metrics*
1. NVIDIA
(NVDA
)
(NVDA )
| 時価総額 | 予想PER（1年） | 1株当たり利益（EPS） |
| 2,179,359,750,000 | 38.31 | $11.94 |
NVIDIA has been at the forefront of AI development, leveraging its powerful GPU technology to advance various sectors, including healthcare. In healthcare, NVIDIA’s AI platforms are used to accelerate drug discovery, medical imaging, and genetic analysis. For instance, their GPUs enable faster processing of large datasets for tasks like imaging diagnostics, helping to identify diseases from X-rays and MRIs with greater accuracy and speed.
NVIDIA collaborates with research institutions and healthcare organizations to develop AI tools that predict diseases, improve patient outcomes, and reduce healthcare costs. Through these initiatives, NVIDIA enhances existing healthcare applications and pioneers new ways to diagnose and treat diseases using the power of AI.
At the time of writing, NVDA was listed by the majority of analysts as a ‘強く買い’
2. Powerful Medical
The flagship product/service of Powerful Medical is known as PMCardio. This is a platform designed to assist healthcare professionals in analyzing, interpreting, diagnosing, and treating cardiac events.
It uses machine learning to analyze ECGs and compare them against a vast database of patient records. This allows PMcardio to detect myocardial infarctions, aka ‘heart attacks’, and other abnormalities accurately and quickly.
The platform stands out for its ability to provide precise diagnoses at the initial point of contact, which is crucial for timely intervention in cardiovascular emergencies. PMcardio’s technology is particularly significant because it helps to address the critical gap in detecting heart conditions that may not be apparent through traditional diagnostic methods.
By integrating AI into its operations, PMcardio offers healthcare professionals a powerful tool that improves care coordination, streams the triage process, and ensures early and accurate detection of potentially life‑threatening cardiac events. This advancement in medical technology highlights the potential of AI to revolutionize the field of cardiovascular diagnostics by enhancing the capability to predict and treat heart diseases effectively.
As recently as 2024年3月1日, PMcardio has managed to 欧州イノベーション委員会から750万ユーロの資金調達に成功し、AIベースの診断ツールの開発を継続しています。これは、世界の主要な死亡原因の一つを軽減する可能性を示しています。
